Accepted papers
Certifications. Accepted TMLR papers can be awareded a number of certifications by the action editors or editors-in-chief of TMLR. The current list of awarded certificates is (click on the badges to see the papers with the certification):
- Featured This certification may be awarded to papers that are very high quality. These papers present significant contributions which are novel, clearly explained, and well supported with evidence, theory, or analysis. If this paper was submitted to a top-tier conference, it would likely be presented as an oral/spotlight.
- Reproducibility This is awarded to papers whose primary purpose is reproduction of other published work. Beyond simple verification, the paper must contribute significant added value through additional baselines, analysis, ablations, or insights. Survey Certification. Papers that not only meet the criteria for acceptance but also provide an exceptionally thorough or insightful survey of the topic or approach may be awarded this certification.
- Survey The Survey Certificate is awareded to papers that not only meet the criteria for acceptance but also provide an exceptionally thorough or insightful survey of the topic or approach may be awarded this certification.
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Containing a spread through sequential learning: to exploit or to explore?
Xingran Chen, Hesam Nikpey, Jungyeol Kim, Saswati Sarkar, Shirin Saeedi Bidokhti, March 2023
[openreview] [pdf] [bib] [code] -
Bidirectional View based Consistency Regularization for Semi-Supervised Domain Adaptation
Yuntao Du, 娟 江, Hongtao Luo, Haiyang Yang, MingCai Chen, Chongjun Wang, March 2023
[openreview] [pdf] [bib] -
Improving Generalization with Approximate Factored Value Functions
Shagun Sodhani, Sergey Levine, Amy Zhang, March 2023
[openreview] [pdf] [bib] -
FLUID: A Unified Evaluation Framework for Flexible Sequential Data
Matthew Wallingford, Aditya Kusupati, Keivan Alizadeh-Vahid, Aaron Walsman, Aniruddha Kembhavi, Ali Farhadi, March 2023
[openreview] [pdf] [bib] [code] -
The Low-Rank Simplicity Bias in Deep Networks
Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola, March 2023
[openreview] [pdf] [bib] -
Identification of Negative Transfers in Multitask Learning Using Surrogate Models
Dongyue Li, Huy Nguyen, Hongyang Ryan Zhang, March 2023
[openreview] [pdf] [bib] [code]
Certifications: Featured -
Multi-objective Bayesian Optimization with Heuristic Objectives for Biomedical and Molecular Data Analysis Workflows
Alina Selega, Kieran R. Campbell, March 2023
[openreview] [pdf] [bib] [code] -
Parameter Efficient Node Classification on Homophilic Graphs
Lucas Prieto, Jeroen Den Boef, Paul Groth, Joran Cornelisse, March 2023
[openreview] [pdf] [bib] [code] -
Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks
Sadegh Mahdavi, Kevin Swersky, Thomas Kipf, Milad Hashemi, Christos Thrampoulidis, Renjie Liao, March 2023
[openreview] [pdf] [bib] [code] -
L-SVRG and L-Katyusha with Adaptive Sampling
Boxin Zhao, Boxiang Lyu, mladen kolar, March 2023
[openreview] [pdf] [bib] -
Quantum Policy Iteration via Amplitude Estimation and Grover Search – Towards Quantum Advantage for Reinforcement Learning
Simon Wiedemann, Daniel Hein, Steffen Udluft, Christian B. Mendl, March 2023
[openreview] [pdf] [bib] -
Patches Are All You Need?
Asher Trockman, J Zico Kolter, March 2023
[openreview] [pdf] [bib]
Certifications: Featured -
Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance
Bahjat Kawar, Roy Ganz, Michael Elad, March 2023
[openreview] [pdf] [bib] -
Improved Overparametrization Bounds for Global Convergence of SGD for Shallow Neural Networks
Bartłomiej Polaczyk, Jacek Cyranka, March 2023
[openreview] [pdf] [bib] [code] -
PRUDEX-Compass: Towards Systematic Evaluation of Reinforcement Learning in Financial Markets
Shuo Sun, Molei Qin, Xinrun Wang, Bo An, March 2023
[openreview] [pdf] [bib] [code]
Certifications: Reproducibility -
A Unified View of Masked Image Modeling
Zhiliang Peng, Li Dong, Hangbo Bao, Furu Wei, Qixiang Ye, March 2023
[openreview] [pdf] [bib] [code] -
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts
Haotao Wang, Junyuan Hong, Jiayu Zhou, Zhangyang Wang, March 2023
[openreview] [pdf] [bib] -
Leveraging Demonstrations with Latent Space Priors
Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause, Gabriel Synnaeve, Nicolas Usunier, March 2023
[openreview] [pdf] [bib] [code] -
Solving Nonconvex-Nonconcave Min-Max Problems exhibiting Weak Minty Solutions
Axel Böhm, March 2023
[openreview] [pdf] [bib] [code] -
Extreme Masking for Learning Instance and Distributed Visual Representations
Zhirong Wu, Zihang Lai, Xiao Sun, Stephen Lin, March 2023
[openreview] [pdf] [bib] [code] -
Temperature check: theory and practice for training models with softmax-cross-entropy losses
Atish Agarwala, Samuel Stern Schoenholz, Jeffrey Pennington, Yann Dauphin, March 2023
[openreview] [pdf] [bib] -
Fusion of Global and Local Knowledge for Personalized Federated Learning
Tiansheng Huang, Li Shen, Yan Sun, Weiwei Lin, Dacheng Tao, March 2023
[openreview] [pdf] [bib] [code] -
Defense Against Reward Poisoning Attacks in Reinforcement Learning
Kiarash Banihashem, Adish Singla, Goran Radanovic, March 2023
[openreview] [pdf] [bib] -
Learning Energy Conserving Dynamics Efficiently with Hamiltonian Gaussian Processes
Magnus Ross, Markus Heinonen, March 2023
[openreview] [pdf] [bib] [code] -
Continual Learning by Modeling Intra-Class Variation
Longhui Yu, Tianyang Hu, Lanqing HONG, Zhen Liu, Adrian Weller, Weiyang Liu, March 2023
[openreview] [pdf] [bib] [code] -
Costs and Benefits of Fair Regression
Han Zhao, March 2023
[openreview] [pdf] [bib] -
Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer
Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake Aaron Richards, March 2023
[openreview] [pdf] [bib] [code] -
Transductive Decoupled Variational Inference for Few-Shot Classification
Anuj Rajeeva Singh, Hadi Jamali-Rad, March 2023
[openreview] [pdf] [bib] [code] -
Black-Box Prompt Learning for Pre-trained Language Models
Shizhe Diao, Zhichao Huang, Ruijia Xu, Xuechun Li, LIN Yong, Xiao Zhou, Tong Zhang, March 2023
[openreview] [pdf] [bib] -
Numerical Accounting in the Shuffle Model of Differential Privacy
Antti Koskela, Mikko A. Heikkilä, Antti Honkela, March 2023
[openreview] [pdf] [bib] [code]
Certifications: Featured -
Image Compression with Product Quantized Masked Image Modeling
Alaaeldin El-Nouby, Matthew J. Muckley, Karen Ullrich, Ivan Laptev, Jakob Verbeek, Herve Jegou, March 2023
[openreview] [pdf] [bib] -
A Cubic Regularization Approach for Finding Local Minimax Points in Nonconvex Minimax Optimization
Ziyi Chen, Zhengyang Hu, Qunwei Li, Zhe Wang, Yi Zhou, March 2023
[openreview] [pdf] [bib] [code] -
Action Poisoning Attacks on Linear Contextual Bandits
Guanlin Liu, Lifeng Lai, March 2023
[openreview] [pdf] [bib] -
Mixed effects in machine learning – A flexible mixedML framework to add random effects to supervised machine learning regression
Pascal Kilian, Sangbeak Ye, Augustin Kelava, March 2023
[openreview] [pdf] [bib] -
Probing Predictions on OOD Images via Nearest Categories
Yao-Yuan Yang, Cyrus Rashtchian, Ruslan Salakhutdinov, Kamalika Chaudhuri, March 2023
[openreview] [pdf] [bib] [code] -
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems
Andreas Look, Barbara Rakitsch, Melih Kandemir, Jan Peters, March 2023
[openreview] [pdf] [bib] [code] -
Better Theory for SGD in the Nonconvex World
Ahmed Khaled, Peter Richtárik, March 2023
[openreview] [pdf] [bib]
Certifications: Survey -
Solving a Special Type of Optimal Transport Problem by a Modified Hungarian Algorithm
Yiling Xie, Yiling Luo, Xiaoming Huo, March 2023
[openreview] [pdf] [bib] -
AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods
Zheng Shi, Abdurakhmon Sadiev, Nicolas Loizou, Peter Richtárik, Martin Takáč, February 2023
[openreview] [pdf] [bib] [code] -
U-Statistics for Importance-Weighted Variational Inference
Javier Burroni, Kenta Takatsu, Justin Domke, Daniel Sheldon, February 2023
[openreview] [pdf] [bib] -
OADAT: Experimental and Synthetic Clinical Optoacoustic Data for Standardized Image Processing
Firat Ozdemir, Berkan Lafci, Xose Luis Dean-Ben, Daniel Razansky, Fernando Perez-Cruz, February 2023
[openreview] [pdf] [bib] [code] -
Stacking Diverse Architectures to Improve Machine Translation
Andrea Schioppa, Nal Kalchbrenner, February 2023
[openreview] [pdf] [bib] [code] -
Contrastive Search Is What You Need For Neural Text Generation
Yixuan Su, Nigel Collier, February 2023
[openreview] [pdf] [bib] [code] -
Separable Self-attention for Mobile Vision Transformers
Sachin Mehta, Mohammad Rastegari, February 2023
[openreview] [pdf] [bib] [code] -
A Flexible Nadaraya-Watson Head Can Offer Explainable and Calibrated Classification
Alan Q. Wang, Mert R. Sabuncu, February 2023
[openreview] [pdf] [bib] [code] -
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models
Juan Lopez Alcaraz, Nils Strodthoff, February 2023
[openreview] [pdf] [bib] [code] -
Robust Hybrid Learning With Expert Augmentation
Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Joern-Henrik Jacobsen, February 2023
[openreview] [pdf] [bib] -
Improved Differentially Private Riemannian Optimization: Fast Sampling and Variance Reduction
Saiteja Utpala, Andi Han, Pratik Jawanpuria, Bamdev Mishra, February 2023
[openreview] [pdf] [bib] -
Dirichlet Mechanism for Differentially Private KL Divergence Minimization
Donlapark Ponnoprat, February 2023
[openreview] [pdf] [bib] [code] -
Regularized Training of Intermediate Layers for Generative Models for Inverse Problems
Sean Gunn, Jorio Cocola, PAul HAnd, February 2023
[openreview] [pdf] [bib] [code] -
Workflow Discovery from Dialogues in the Low Data Regime
Amine El hattami, Issam H. Laradji, Stefania Raimondo, David Vazquez, Pau Rodriguez, Christopher Pal, February 2023
[openreview] [pdf] [bib] [code]
Certifications: Featured -
Layerwise Bregman Representation Learning of Neural Networks with Applications to Knowledge Distillation
Ehsan Amid, Rohan Anil, Christopher Fifty, Manfred K Warmuth, February 2023
[openreview] [pdf] [bib] -
Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks
Vijaya Raghavan T Ramkumar, Elahe Arani, Bahram Zonooz, February 2023
[openreview] [pdf] [bib] [code] -
KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation
Chenhong Zhou, Feng Liu, Chen Gong, Rongfei Zeng, Tongliang Liu, William Cheung, Bo Han, February 2023
[openreview] [pdf] [bib] [code] -
Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence
Diyuan Wu, Vyacheslav Kungurtsev, Marco Mondelli, February 2023
[openreview] [pdf] [bib] -
DEUP: Direct Epistemic Uncertainty Prediction
Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor I Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio, February 2023
[openreview] [pdf] [bib] [code] -
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan O Arik, Tomas Pfister, February 2023
[openreview] [pdf] [bib]
Certifications: Featured -
Signed Graph Neural Networks: A Frequency Perspective
Rahul Singh, Yongxin Chen, February 2023
[openreview] [pdf] [bib] [code] -
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models
Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Rajiv Didolkar, Dipendra Misra, Dylan J Foster, Lekan P Molu, Rajan Chari, Akshay Krishnamurthy, John Langford, February 2023
[openreview] [pdf] [bib] [code] -
Beyond Intuition: Rethinking Token Attributions inside Transformers
Jiamin Chen, Xuhong Li, Lei Yu, Dejing Dou, Haoyi Xiong, February 2023
[openreview] [pdf] [bib] [code] -
Understanding and Simplifying Architecture Search in Spatio-Temporal Graph Neural Networks
Zhen Xu, quanming yao, Yong Li, Qiang Yang, February 2023
[openreview] [pdf] [bib] [code] -
Finite-Time Analysis of Decentralized Single-Timescale Actor-Critic
qijun luo, Xiao Li, February 2023
[openreview] [pdf] [bib] -
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks
Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond Veldhuis, Decebal Constantin Mocanu, February 2023
[openreview] [pdf] [bib] [code] -
SolidGen: An Autoregressive Model for Direct B-rep Synthesis
Pradeep Kumar Jayaraman, Joseph George Lambourne, Nishkrit Desai, Karl Willis, Aditya Sanghi, Nigel J. W. Morris, February 2023
[openreview] [pdf] [bib]
Certifications: Featured -
Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metric
Saiteja Utpala, Praneeth Vepakomma, Nina Miolane, February 2023
[openreview] [pdf] [bib] -
Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity
Christian Fröhlich, Robert Williamson, February 2023
[openreview] [pdf] [bib] -
Controlling Neural Network Smoothness for Neural Algorithmic Reasoning
David A. Klindt, February 2023
[openreview] [pdf] [bib] [code] -
Target Propagation via Regularized Inversion for Recurrent Neural Networks
Vincent Roulet, Zaid Harchaoui, February 2023
[openreview] [pdf] [bib] [code] -
Bayesian Causal Bandits with Backdoor Adjustment Prior
Jireh Huang, Qing Zhou, January 2023
[openreview] [pdf] [bib] [code] -
Accelerated Quality-Diversity through Massive Parallelism
Bryan Lim, Maxime Allard, Luca Grillotti, Antoine Cully, January 2023
[openreview] [pdf] [bib] [code] -
Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning
Taylor W. Killian, Sonali Parbhoo, Marzyeh Ghassemi, January 2023
[openreview] [pdf] [bib] [code] -
BIGRoC: Boosting Image Generation via a Robust Classifier
Roy Ganz, Michael Elad, January 2023
[openreview] [pdf] [bib] [code] -
Constrained Parameter Inference as a Principle for Learning
Nasir Ahmad, Ellen Schrader, Marcel van Gerven, January 2023
[openreview] [pdf] [bib] [code] -
SMILE: Sample-to-feature Mixup for Efficient Transfer Learning
Xingjian Li, Haoyi Xiong, Cheng-zhong Xu, Dejing Dou, January 2023
[openreview] [pdf] [bib] [code] -
Optimal Convergence Rates of Deep Convolutional Neural Networks: Additive Ridge Functions
Zhiying Fang, Guang Cheng, January 2023
[openreview] [pdf] [bib] -
Dropped Scheduled Task: Mitigating Negative Transfer in Multi-task Learning using Dynamic Task Dropping
Aakarsh Malhotra, Mayank Vatsa, Richa Singh, January 2023
[openreview] [pdf] [bib] [code] -
Revisiting adversarial training for the worst-performing class
Thomas Pethick, Grigorios Chrysos, Volkan Cevher, January 2023
[openreview] [pdf] [bib] [code] -
Calibrate and Debias Layer-wise Sampling for Graph Convolutional Networks
Yifan Chen, Tianning Xu, Dilek Hakkani-Tur, Di Jin, Yun Yang, Ruoqing Zhu, January 2023
[openreview] [pdf] [bib] [code] -
Online Learning for Prediction via Covariance Fitting: Computation, Performance and Robustness
Muhammad Osama, Dave Zachariah, Peter Stoica, Thomas B. Schön, January 2023
[openreview] [pdf] [bib] -
ViViT: Curvature Access Through The Generalized Gauss-Newton’s Low-Rank Structure
Felix Dangel, Lukas Tatzel, Philipp Hennig, January 2023
[openreview] [pdf] [bib] [code] -
On a continuous time model of gradient descent dynamics and instability in deep learning
Mihaela Rosca, Yan Wu, Chongli Qin, Benoit Dherin, January 2023
[openreview] [pdf] [bib] [code] -
Robustness through Data Augmentation Loss Consistency
Tianjian Huang, Shaunak Ashish Halbe, Chinnadhurai Sankar, Pooyan Amini, Satwik Kottur, Alborz Geramifard, Meisam Razaviyayn, Ahmad Beirami, January 2023
[openreview] [pdf] [bib] [code] -
Towards Large Scale Transfer Learning for Differentially Private Image Classification
Harsh Mehta, Abhradeep Guha Thakurta, Alexey Kurakin, Ashok Cutkosky, January 2023
[openreview] [pdf] [bib] [code] -
Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks
Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven, January 2023
[openreview] [pdf] [bib] [code] -
Proportional Fairness in Federated Learning
Guojun Zhang, Saber Malekmohammadi, Xi Chen, Yaoliang Yu, January 2023
[openreview] [pdf] [bib] -
On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks
Franz M. Rohrhofer, Stefan Posch, Clemens Gößnitzer, Bernhard C Geiger, January 2023
[openreview] [pdf] [bib] [code] -
VN-Transformer: Rotation-Equivariant Attention for Vector Neurons
Serge Assaad, Carlton Downey, Rami Al-Rfou', Nigamaa Nayakanti, Benjamin Sapp, January 2023
[openreview] [pdf] [bib] -
lo-fi: distributed fine-tuning without communication
Mitchell Wortsman, Suchin Gururangan, Shen Li, Ali Farhadi, Ludwig Schmidt, Michael Rabbat, Ari S. Morcos, January 2023
[openreview] [pdf] [bib] -
Optimal Threshold Labeling for Ordinal Regression Methods
Ryoya Yamasaki, January 2023
[openreview] [pdf] [bib] [code] -
Recognition Models to Learn Dynamics from Partial Observations with Neural ODEs
Mona Buisson-Fenet, Valery Morgenthaler, Sebastian Trimpe, Florent Di Meglio, January 2023
[openreview] [pdf] [bib] -
Attention Beats Concatenation for Conditioning Neural Fields
Daniel Rebain, Mark J. Matthews, Kwang Moo Yi, Gopal Sharma, Dmitry Lagun, Andrea Tagliasacchi, January 2023
[openreview] [pdf] [bib] -
A Ranking Game for Imitation Learning
Harshit Sikchi, Akanksha Saran, Wonjoon Goo, Scott Niekum, January 2023
[openreview] [pdf] [bib] [code] -
Implicit Ensemble Training for Efficient and Robust Multiagent Reinforcement Learning
Macheng Shen, JONATHAN P HOW, January 2023
[openreview] [pdf] [bib] [code] -
Named Tensor Notation
David Chiang, Alexander M Rush, Boaz Barak, January 2023
[openreview] [pdf] [bib] -
PCPs: Patient Cardiac Prototypes to Probe AI-based Medical Diagnoses, Distill Datasets, and Retrieve Patients
Dani Kiyasseh, Tingting Zhu, David A. Clifton, January 2023
[openreview] [pdf] [bib] -
On the infinite-depth limit of finite-width neural networks
Soufiane Hayou, January 2023
[openreview] [pdf] [bib] -
Intrinsic Dimension for Large-Scale Geometric Learning
Maximilian Stubbemann, Tom Hanika, Friedrich Martin Schneider, January 2023
[openreview] [pdf] [bib] [code] -
Beyond Information Gain: An Empirical Benchmark for Low-Switching-Cost Reinforcement Learning
Shusheng Xu, Yancheng Liang, Yunfei Li, Simon Shaolei Du, Yi Wu, January 2023
[openreview] [pdf] [bib] [code] -
DisCo: Improving Compositional Generalization in Visual Reasoning through Distribution Coverage
Joy Hsu, Jiayuan Mao, Jiajun Wu, January 2023
[openreview] [pdf] [bib] -
Hidden Heterogeneity: When to Choose Similarity-Based Calibration
Kiri L. Wagstaff, Thomas G Dietterich, January 2023
[openreview] [pdf] [bib] [code] -
PolyViT: Co-training Vision Transformers on Images, Videos and Audio
Valerii Likhosherstov, Anurag Arnab, Krzysztof Marcin Choromanski, Mario Lucic, Yi Tay, Mostafa Dehghani, January 2023
[openreview] [pdf] [bib] [code] -
GSR: A Generalized Symbolic Regression Approach
Tony Tohme, Dehong Liu, KAMAL YOUCEF-TOUMI, January 2023
[openreview] [pdf] [bib] -
Bounding generalization error with input compression: An empirical study with infinite-width networks
Angus Galloway, Anna Golubeva, Mahmoud Salem, Mihai Nica, Yani Ioannou, Graham W. Taylor, January 2023
[openreview] [pdf] [bib] [code] -
Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning
Matthew Kyle Schlegel, Volodymyr Tkachuk, Adam M White, Martha White, January 2023
[openreview] [pdf] [bib] [code] -
Learning Representations for Pixel-based Control: What Matters and Why?
Manan Tomar, Utkarsh Aashu Mishra, Amy Zhang, Matthew E. Taylor, January 2023
[openreview] [pdf] [bib] [code] -
FedDAG: Federated DAG Structure Learning
Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard Bondell, January 2023
[openreview] [pdf] [bib] [code] -
Communication-Efficient Distributionally Robust Decentralized Learning
Matteo Zecchin, Marios Kountouris, David Gesbert, January 2023
[openreview] [pdf] [bib] [code] -
EdiBERT: a generative model for image editing
Thibaut Issenhuth, Ugo Tanielian, Jeremie Mary, David Picard, January 2023
[openreview] [pdf] [bib] [code] -
OpenCon: Open-world Contrastive Learning
Yiyou Sun, Yixuan Li, January 2023
[openreview] [pdf] [bib] [code] -
Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks
Jarrod Haas, William Yolland, Bernhard T Rabus, January 2023
[openreview] [pdf] [bib] -
Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization for Low-Rank Tensor Completion and Tensor Robust Principal Component Analysis
Jicong Fan, Lijun Ding, Chengrun Yang, Zhao Zhang, Madeleine Udell, January 2023
[openreview] [pdf] [bib] -
Benchmarks and Algorithms for Offline Preference-Based Reward Learning
Daniel Shin, Anca Dragan, Daniel S. Brown, January 2023
[openreview] [pdf] [bib] [code] -
Fairness and robustness in anti-causal prediction
Maggie Makar, Alexander D'Amour, January 2023
[openreview] [pdf] [bib] -
Uncertainty-Based Active Learning for Reading Comprehension
Jing Wang, Jie Shen, Xiaofei Ma, Andrew Arnold, December 2022
[openreview] [pdf] [bib] [code] -
A geometrical connection between sparse and low-rank matrices and its application to manifold learning
Lawrence K. Saul, December 2022
[openreview] [pdf] [bib] -
Collaborative Algorithms for Online Personalized Mean Estimation
Mahsa Asadi, Aurélien Bellet, Odalric-Ambrym Maillard, Marc Tommasi, December 2022
[openreview] [pdf] [bib] [code] -
Indiscriminate Data Poisoning Attacks on Neural Networks
Yiwei Lu, Gautam Kamath, Yaoliang Yu, December 2022
[openreview] [pdf] [bib] -
An empirical study of implicit regularization in deep offline RL
Caglar Gulcehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet, December 2022
[openreview] [pdf] [bib] -
On Characterizing the Trade-off in Invariant Representation Learning
Bashir Sadeghi, Sepehr Dehdashtian, Vishnu Boddeti, December 2022
[openreview] [pdf] [bib] [code]
Certifications: Featured -
Unsupervised Network Embedding Beyond Homophily
Zhiqiang Zhong, Guadalupe Gonzalez, Daniele Grattarola, Jun Pang, December 2022
[openreview] [pdf] [bib] -
Unsupervised Learning of Neurosymbolic Encoders
Eric Zhan, Jennifer J. Sun, Ann Kennedy, Yisong Yue, Swarat Chaudhuri, December 2022
[openreview] [pdf] [bib] [code] -
Sequentially learning the topological ordering of directed acyclic graphs with likelihood ratio scores
Gabriel Ruiz, OSCAR HERNAN MADRID PADILLA, Qing Zhou, December 2022
[openreview] [pdf] [bib] [code] -
A Snapshot of the Frontiers of Client Selection in Federated Learning
Gergely Dániel Németh, Miguel Angel Lozano, Novi Quadrianto, Nuria M Oliver, December 2022
[openreview] [pdf] [bib]
Certifications: Survey -
Object-aware Cropping for Self-Supervised Learning
Shlok Kumar Mishra, Anshul Shah, Ankan Bansal, Janit K Anjaria, Abhyuday Narayan Jagannatha, Abhishek Sharma, David Jacobs, Dilip Krishnan, December 2022
[openreview] [pdf] [bib] [code] -
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty
Thomas George, Guillaume Lajoie, Aristide Baratin, December 2022
[openreview] [pdf] [bib] [code] -
Fourier Sensitivity and Regularization of Computer Vision Models
Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo, December 2022
[openreview] [pdf] [bib] [code] -
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that Matter
Jaime Spencer, Chris Russell, Simon Hadfield, Richard Bowden, December 2022
[openreview] [pdf] [bib] [code]
Certifications: Reproducibility -
MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth
Chenjie Cao, Xinlin Ren, Yanwei Fu, December 2022
[openreview] [pdf] [bib] [code] -
Controllable Generative Modeling via Causal Reasoning
Joey Bose, Ricardo Pio Monti, Aditya Grover, December 2022
[openreview] [pdf] [bib] -
A Stochastic Optimization Framework for Fair Risk Minimization
Andrew Lowy, Sina Baharlouei, Rakesh Pavan, Meisam Razaviyayn, Ahmad Beirami, December 2022
[openreview] [pdf] [bib] [code] -
Modeling Bounded Rationality in Multi-Agent Simulations Using Rationally Inattentive Reinforcement Learning
Tong Mu, Stephan Zheng, Alexander R Trott, December 2022
[openreview] [pdf] [bib] -
Calibrated Selective Classification
Adam Fisch, Tommi S. Jaakkola, Regina Barzilay, December 2022
[openreview] [pdf] [bib] [code] -
Unsupervised Mismatch Localization in Cross-Modal Sequential Data with Application to Mispronunciations Localization
Wei Wei, Hengguan Huang, Xiangming Gu, Hao Wang, Ye Wang, December 2022
[openreview] [pdf] [bib] -
GIT: A Generative Image-to-text Transformer for Vision and Language
Jianfeng Wang, Zhengyuan Yang, Xiaowei Hu, Linjie Li, Kevin Lin, Zhe Gan, Zicheng Liu, Ce Liu, Lijuan Wang, December 2022
[openreview] [pdf] [bib] -
Concave Utility Reinforcement Learning with Zero-Constraint Violations
Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal, December 2022
[openreview] [pdf] [bib] -
Fast and Accurate Spreading Process Temporal Scale Estimation
Abram Magner, Carolyn S Kaminski, Petko Bogdanov, December 2022
[openreview] [pdf] [bib] [code] -
Extracting Local Reasoning Chains of Deep Neural Networks
Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang, December 2022
[openreview] [pdf] [bib] -
On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces
Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh, December 2022
[openreview] [pdf] [bib] -
Distribution Embedding Networks for Generalization from a Diverse Set of Classification Tasks
Lang Liu, Mahdi Milani Fard, Sen Zhao, December 2022
[openreview] [pdf] [bib] -
COIN++: Neural Compression Across Modalities
Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet, December 2022
[openreview] [pdf] [bib] [code] -
Systematically and efficiently improving $k$-means initialization by pairwise-nearest-neighbor smoothing
Carlo Baldassi, December 2022
[openreview] [pdf] [bib] [code] -
GhostSR: Learning Ghost Features for Efficient Image Super-Resolution
Ying Nie, Kai Han, Zhenhua Liu, Chuanjian Liu, Yunhe Wang, December 2022
[openreview] [pdf] [bib] [code] -
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents
Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar, December 2022
[openreview] [pdf] [bib] [code] -
On the Origins of the Block Structure Phenomenon in Neural Network Representations
Thao Nguyen, Maithra Raghu, Simon Kornblith, December 2022
[openreview] [pdf] [bib] -
Interpretable Node Representation with Attribute Decoding
Xiaohui Chen, Xi Chen, Liping Liu, December 2022
[openreview] [pdf] [bib] -
A Unified Domain Adaptation Framework with Distinctive Divergence Analysis
Zhiri YUAN, Xixu HU, Qi WU, Shumin MA, Cheuk Hang LEUNG, Xin Shen, Yiyan HUANG, December 2022
[openreview] [pdf] [bib] -
Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions
Alberto Bordino, Stefano Favaro, Sandra Fortini, December 2022
[openreview] [pdf] [bib] -
Counterfactual Learning with Multioutput Deep Kernels
Alberto Caron, Ioanna Manolopoulou, Gianluca Baio, December 2022
[openreview] [pdf] [bib] -
Incorporating Sum Constraints into Multitask Gaussian Processes
Philipp Pilar, Carl Jidling, Thomas B. Schön, Niklas Wahlström, December 2022
[openreview] [pdf] [bib] [code] -
Degradation Attacks on Certifiably Robust Neural Networks
Klas Leino, Chi Zhang, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina Pasareanu, November 2022
[openreview] [pdf] [bib] [code] -
If your data distribution shifts, use self-learning
Evgenia Rusak, Steffen Schneider, George Pachitariu, Luisa Eck, Peter Vincent Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge, November 2022
[openreview] [pdf] [bib] [code] -
An approximate sampler for energy-based models with divergence diagnostics
Bryan Eikema, Germán Kruszewski, Christopher R Dance, Hady Elsahar, Marc Dymetman, November 2022
[openreview] [pdf] [bib] [code] -
A Unified Survey on Anomaly, Novelty, Open-Set, and Out of-Distribution Detection: Solutions and Future Challenges
Mohammadreza Salehi, Hossein Mirzaei, Dan Hendrycks, Yixuan Li, Mohammad Hossein Rohban, Mohammad Sabokrou, November 2022
[openreview] [pdf] [bib] [code] -
Bayesian Methods for Constraint Inference in Reinforcement Learning
Dimitris Papadimitriou, Usman Anwar, Daniel S. Brown, November 2022
[openreview] [pdf] [bib] [code] -
A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful
Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Volodimir Begy, Gilles Louppe, November 2022
[openreview] [pdf] [bib] [code] -
On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning
Lu Han, Han-Jia Ye, De-Chuan Zhan, November 2022
[openreview] [pdf] [bib] -
Reinventing Policy Iteration under Time Inconsistency
Nixie S Lesmana, Huangyuan Su, Chi Seng Pun, November 2022
[openreview] [pdf] [bib] [code] -
Nonparametric Learning of Two-Layer ReLU Residual Units
Zhunxuan Wang, Linyun He, Chunchuan Lyu, Shay B Cohen, November 2022
[openreview] [pdf] [bib] [code] -
Stochastic Douglas-Rachford Splitting for Regularized Empirical Risk Minimization: Convergence, Mini-batch, and Implementation
Aysegul Bumin, Kejun Huang, November 2022
[openreview] [pdf] [bib] [code] -
Does Entity Abstraction Help Generative Transformers Reason?
Nicolas Gontier, Siva Reddy, Christopher Pal, November 2022
[openreview] [pdf] [bib] -
Complex-Valued Autoencoders for Object Discovery
Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling, November 2022
[openreview] [pdf] [bib] [code] -
Learning Algorithms for Markovian Bandits:\\Is Posterior Sampling more Scalable than Optimism?
Nicolas Gast, Bruno Gaujal, Kimang Khun, November 2022
[openreview] [pdf] [bib] [code] -
Modeling Object Dissimilarity for Deep Saliency Prediction
Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Seungryong Kim, Mathieu Salzmann, Sabine Süsstrunk, November 2022
[openreview] [pdf] [bib] [code] -
Optimizing Intermediate Representations of Generative Models for Phase Retrieval
Tobias Uelwer, Sebastian Konietzny, Stefan Harmeling, November 2022
[openreview] [pdf] [bib] -
Algorithms and Theory for Supervised Gradual Domain Adaptation
Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao, November 2022
[openreview] [pdf] [bib] -
Teacher’s pet: understanding and mitigating biases in distillation
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar, November 2022
[openreview] [pdf] [bib] -
Action Noise in Off-Policy Deep Reinforcement Learning: Impact on Exploration and Performance
Jakob Hollenstein, Sayantan Auddy, Matteo Saveriano, Erwan Renaudo, Justus Piater, November 2022
[openreview] [pdf] [bib] [code]
Certifications: Survey -
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities
Andreas Kirsch, Yarin Gal, November 2022
[openreview] [pdf] [bib] [code] -
An Efficient One-Class SVM for Novelty Detection in IoT
Kun Yang, Samory Kpotufe, Nick Feamster, November 2022
[openreview] [pdf] [bib] -
Competition over data: how does data purchase affect users?
Yongchan Kwon, Tony A Ginart, James Zou, November 2022
[openreview] [pdf] [bib] [code] -
Diffusion Models for Video Prediction and Infilling
Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi, November 2022
[openreview] [pdf] [bib] -
Efficient Gradient Flows in Sliced-Wasserstein Space
Clément Bonet, Nicolas Courty, François Septier, Lucas Drumetz, November 2022
[openreview] [pdf] [bib] [code] -
Approximate Policy Iteration with Bisimulation Metrics
Mete Kemertas, Allan Douglas Jepson, November 2022
[openreview] [pdf] [bib] [code] -
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images
Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus Robert Muller, Marius Kloft, November 2022
[openreview] [pdf] [bib] [code] -
Mitigating Catastrophic Forgetting in Spiking Neural Networks through Threshold Modulation
Ilyass Hammouamri, Timothée Masquelier, Dennis George Wilson, November 2022
[openreview] [pdf] [bib] [code] -
A Generalist Agent
Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-maron, Mai Giménez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas, November 2022
[openreview] [pdf] [bib]
Certifications: Featured -
ZerO Initialization: Initializing Neural Networks with only Zeros and Ones
Jiawei Zhao, Florian Tobias Schaefer, Anima Anandkumar, November 2022
[openreview] [pdf] [bib] [code] -
A Rigorous Study Of The Deep Taylor Decomposition
Leon Sixt, Tim Landgraf, November 2022
[openreview] [pdf] [bib] [code] -
Convergence of denoising diffusion models under the manifold hypothesis
Valentin De Bortoli, November 2022
[openreview] [pdf] [bib] -
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, Yonghui Wu, November 2022
[openreview] [pdf] [bib]
Certifications: Featured -
Fail-Safe Adversarial Generative Imitation Learning
Philipp Geiger, Christoph-Nikolas Straehle, November 2022
[openreview] [pdf] [bib] [code] -
A Note on "Assessing Generalization of SGD via Disagreement"
Andreas Kirsch, Yarin Gal, November 2022
[openreview] [pdf] [bib] [code] -
DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture
kaichen zhou, Lanqing HONG, Shoukang Hu, Fengwei Zhou, Binxin Ru, Jiashi Feng, Zhenguo Li, November 2022
[openreview] [pdf] [bib] [code] -
Data Leakage in Federated Averaging
Dimitar Iliev Dimitrov, Mislav Balunovic, Nikola Konstantinov, Martin Vechev, November 2022
[openreview] [pdf] [bib] [code] -
On the Adversarial Robustness of Vision Transformers
Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh, November 2022
[openreview] [pdf] [bib] [code] -
Behind the Machine’s Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention
Leo Schwinn, Doina Precup, Bjoern Eskofier, Dario Zanca, October 2022
[openreview] [pdf] [bib] [code] -
Structured Uncertainty in the Observation Space of Variational Autoencoders
James Langley, Miguel Monteiro, Charles Jones, Nick Pawlowski, Ben Glocker, October 2022
[openreview] [pdf] [bib] [code] -
Distributed Stochastic Algorithms for High-rate Streaming Principal Component Analysis
Haroon Raja, Waheed Bajwa, October 2022
[openreview] [pdf] [bib] [code] -
Benchmarking Progress to Infant-Level Physical Reasoning in AI
Luca Weihs, Amanda Yuile, Renée Baillargeon, Cynthia Fisher, Gary Marcus, Roozbeh Mottaghi, Aniruddha Kembhavi, October 2022
[openreview] [pdf] [bib] [code] -
Linear algebra with transformers
Francois Charton, October 2022
[openreview] [pdf] [bib] -
INR-V: A Continuous Representation Space for Video-based Generative Tasks
Bipasha Sen, Aditya Agarwal, Vinay P Namboodiri, C.V. Jawahar, October 2022
[openreview] [pdf] [bib] [code] -
A Simple Convergence Proof of Adam and Adagrad
Alexandre Défossez, Leon Bottou, Francis Bach, Nicolas Usunier, October 2022
[openreview] [pdf] [bib] -
On the Paradox of Certified Training
Nikola Jovanović, Mislav Balunovic, Maximilian Baader, Martin Vechev, October 2022
[openreview] [pdf] [bib] [code] -
Time Series Alignment with Global Invariances
Titouan Vayer, Romain Tavenard, Laetitia Chapel, Rémi Flamary, Nicolas Courty, Yann Soullard, October 2022
[openreview] [pdf] [bib] [code] -
Explicit Group Sparse Projection with Applications to Deep Learning and NMF
Riyasat Ohib, Nicolas Gillis, Niccolo Dalmasso, Sameena Shah, Vamsi K. Potluru, Sergey Plis, October 2022
[openreview] [pdf] [bib] [code] -
Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning
Baijiong Lin, Feiyang YE, Yu Zhang, Ivor Tsang, October 2022
[openreview] [pdf] [bib] -
Direct Molecular Conformation Generation
Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Tao Qin, Wengang Zhou, Houqiang Li, Haiguang Liu, Tie-Yan Liu, October 2022
[openreview] [pdf] [bib] [code] -
Symbolic Regression is NP-hard
Marco Virgolin, Solon P Pissis, October 2022
[openreview] [pdf] [bib] -
Differentially Private Stochastic Expectation Propagation
Margarita Vinaroz, Mijung Park, October 2022
[openreview] [pdf] [bib] -
Practicality of generalization guarantees for unsupervised domain adaptation with neural networks
Adam Breitholtz, Fredrik Daniel Johansson, October 2022
[openreview] [pdf] [bib] [code] -
On Noise Abduction for Answering Counterfactual Queries: A Practical Outlook
Saptarshi Saha, Utpal Garain, October 2022
[openreview] [pdf] [bib] [code] -
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed
Mélanie Bernhardt, Fabio De Sousa Ribeiro, Ben Glocker, October 2022
[openreview] [pdf] [bib] -
Bridging Offline and Online Experimentation: Constraint Active Search for Deployed Performance Optimization
Junpei Komiyama, Gustavo Malkomes, Bolong Cheng, Michael McCourt, October 2022
[openreview] [pdf] [bib] -
Multi-Source Causal Inference Using Control Variates under Outcome Selection Bias
Wenshuo Guo, Serena Lutong Wang, Peng Ding, Yixin Wang, Michael Jordan, October 2022
[openreview] [pdf] [bib] -
Identifiable Deep Generative Models via Sparse Decoding
Gemma Elyse Moran, Dhanya Sridhar, Yixin Wang, David Blei, October 2022
[openreview] [pdf] [bib] [code] -
Using unsupervised learning to detect broken symmetries, with relevance to searches for parity violation in nature.
Christopher Gorham Lester, October 2022
[openreview] [pdf] [bib] [code] -
Integrating Rankings into Quantized Scores in Peer Review
Yusha Liu, Yichong Xu, Nihar B Shah, Aarti Singh, October 2022
[openreview] [pdf] [bib] -
Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning
Linfeng Liu, XU HAN, Dawei Zhou, Liping Liu, October 2022
[openreview] [pdf] [bib] [code] -
Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning
Tongzhou Mu, Kaixiang Lin, Feiyang Niu, Govind Thattai, October 2022
[openreview] [pdf] [bib] -
Secure Domain Adaptation with Multiple Sources
Serban Stan, Mohammad Rostami, October 2022
[openreview] [pdf] [bib] -
Teaching Models to Express Their Uncertainty in Words
Stephanie Lin, Jacob Hilton, Owain Evans, October 2022
[openreview] [pdf] [bib] [code] -
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning
Philipp Becker, Gerhard Neumann, October 2022
[openreview] [pdf] [bib] [code] -
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning
Anders Johan Andreassen, Yasaman Bahri, Behnam Neyshabur, Rebecca Roelofs, October 2022
[openreview] [pdf] [bib] -
Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation
Zhiqiang Zhong, Sergei Ivanov, Jun Pang, October 2022
[openreview] [pdf] [bib] -
Centroids Matching: an efficient Continual Learning approach operating in the embedding space
Jary Pomponi, Simone Scardapane, Aurelio Uncini, October 2022
[openreview] [pdf] [bib] [code] -
Nonstationary Reinforcement Learning with Linear Function Approximation
Huozhi Zhou, Jinglin Chen, Lav R. Varshney, Ashish Jagmohan, October 2022
[openreview] [pdf] [bib] -
Enhanced gradient-based MCMC in discrete spaces
Benjamin Rhodes, Michael U. Gutmann, October 2022
[openreview] [pdf] [bib] -
Flipped Classroom: Effective Teaching for Time Series Forecasting
Philipp Teutsch, Patrick Mäder, October 2022
[openreview] [pdf] [bib] [code] -
Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach
Mohammad Ali Alomrani, Reza Moravej, Elias Boutros Khalil, October 2022
[openreview] [pdf] [bib] [code] -
Generative Adversarial Neural Operators
Md Ashiqur Rahman, Manuel A Florez, Anima Anandkumar, Zachary E Ross, Kamyar Azizzadenesheli, October 2022
[openreview] [pdf] [bib] [code] -
Lookback for Learning to Branch
Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar, October 2022
[openreview] [pdf] [bib] -
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality
Fusheng Liu, Haizhao Yang, Soufiane Hayou, Qianxiao Li, October 2022
[openreview] [pdf] [bib] [code] -
Unimodal Likelihood Models for Ordinal Data
Ryoya Yamasaki, October 2022
[openreview] [pdf] [bib] [code] -
Differentiable Model Compression via Pseudo Quantization Noise
Alexandre Défossez, Yossi Adi, Gabriel Synnaeve, October 2022
[openreview] [pdf] [bib] [code] -
Local Kernel Ridge Regression for Scalable, Interpolating, Continuous Regression
Mingxuan Han, Chenglong Ye, Jeff Phillips, October 2022
[openreview] [pdf] [bib] -
Mace: A flexible framework for membership privacy estimation in generative models
Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul M Dodhia, Juan M Lavista Ferres, October 2022
[openreview] [pdf] [bib] -
Fingerprints of Super Resolution Networks
Jeremy Vonderfecht, Feng Liu, October 2022
[openreview] [pdf] [bib] [code] -
Online Double Oracle
Le Cong Dinh, Stephen Marcus McAleer, Zheng Tian, Nicolas Perez-Nieves, Oliver Slumbers, David Henry Mguni, Jun Wang, Haitham Bou Ammar, Yaodong Yang, October 2022
[openreview] [pdf] [bib] [code] -
Attribute Prediction as Multiple Instance Learning
Diego Marcos, Aike Potze, Wenjia Xu, Devis Tuia, Zeynep Akata, October 2022
[openreview] [pdf] [bib] [code] -
Completeness and Coherence Learning for Fast Arbitrary Style Transfer
Zhijie Wu, Chunjin Song, Guanxiong Chen, Sheng Guo, Weilin Huang, October 2022
[openreview] [pdf] [bib] [code] -
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification
Gabriel Bénédict, Hendrik Vincent Koops, Daan Odijk, Maarten de Rijke, October 2022
[openreview] [pdf] [bib] [code] -
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data
Eugenia Iofinova, Nikola Konstantinov, Christoph H Lampert, October 2022
[openreview] [pdf] [bib] [code] -
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets
Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary Ward Ulissi, C. Lawrence Zitnick, Abhishek Das, October 2022
[openreview] [pdf] [bib] [code] -
MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks
Ali Ramezani-Kebrya, Iman Tabrizian, Fartash Faghri, Petar Popovski, October 2022
[openreview] [pdf] [bib] [code] -
LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling
Jinsung Yoon, Sercan O Arik, Tomas Pfister, September 2022
[openreview] [pdf] [bib] -
Sparse MoEs meet Efficient Ensembles
James Urquhart Allingham, Florian Wenzel, Zelda E Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton, September 2022
[openreview] [pdf] [bib] [code] -
FedShuffle: Recipes for Better Use of Local Work in Federated Learning
Samuel Horváth, Maziar Sanjabi, Lin Xiao, Peter Richtárik, Michael Rabbat, September 2022
[openreview] [pdf] [bib] -
Representation Alignment in Neural Networks
Ehsan Imani, Wei Hu, Martha White, September 2022
[openreview] [pdf] [bib] [code] -
Faking Interpolation Until You Make It
Alasdair Paren, Rudra P. K. Poudel, M. Pawan Kumar, September 2022
[openreview] [pdf] [bib] [code] -
Ensembles of Classifiers: a Bias-Variance Perspective
Neha Gupta, Jamie Smith, Ben Adlam, Zelda E Mariet, September 2022
[openreview] [pdf] [bib] -
GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation
Haibo Qiu, Baosheng Yu, Dacheng Tao, September 2022
[openreview] [pdf] [bib] [code] -
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure
Samuel Kim, Peter Y Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic, September 2022
[openreview] [pdf] [bib] [code] -
Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning
Fan Wang, Hao Tian, Haoyi Xiong, Hua Wu, Jie Fu, Yang Cao, Kang Yu, Haifeng Wang, September 2022
[openreview] [pdf] [bib] [code] -
Multitask Online Mirror Descent
Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, massimiliano pontil, September 2022
[openreview] [pdf] [bib] -
Approximating 1-Wasserstein Distance with Trees
Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi, September 2022
[openreview] [pdf] [bib] [code] -
Do better ImageNet classifiers assess perceptual similarity better?
Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin Dogus Cubuk, September 2022
[openreview] [pdf] [bib] [code] -
Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent
Ajaykrishna Karthikeyan, Naman Jain, Nagarajan Natarajan, Prateek Jain, September 2022
[openreview] [pdf] [bib] [code] -
Probabilistic Autoencoder
Vanessa M Boehm, Uros Seljak, September 2022
[openreview] [pdf] [bib] [code] -
Decoder Denoising Pretraining for Semantic Segmentation
Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi, September 2022
[openreview] [pdf] [bib] -
Can You Win Everything with A Lottery Ticket?
Tianlong Chen, Zhenyu Zhang, Jun Wu, Randy Huang, Sijia Liu, Shiyu Chang, Zhangyang Wang, September 2022
[openreview] [pdf] [bib] [code] -
HEAT: Hyperedge Attention Networks
Dobrik Georgiev Georgiev, Marc Brockschmidt, Miltiadis Allamanis, September 2022
[openreview] [pdf] [bib] [code] -
On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning
Washim Uddin Mondal, Vaneet Aggarwal, Satish Ukkusuri, September 2022
[openreview] [pdf] [bib] [code] -
Exploring Efficient Few-shot Adaptation for Vision Transformers
Chengming Xu, Siqian Yang, Yabiao Wang, Zhanxiong Wang, Yanwei Fu, Xiangyang Xue, September 2022
[openreview] [pdf] [bib] -
Weight Expansion: A New Perspective on Dropout and Generalization
Gaojie Jin, Xinping Yi, Pengfei Yang, Lijun Zhang, Sven Schewe, Xiaowei Huang, September 2022
[openreview] [pdf] [bib] [code] -
Exploring the Learning Mechanisms of Neural Division Modules
Bhumika Mistry, Katayoun Farrahi, Jonathon Hare, September 2022
[openreview] [pdf] [bib] [code] -
Domain Invariant Adversarial Learning
Matan Levi, Idan Attias, Aryeh Kontorovich, September 2022
[openreview] [pdf] [bib] [code] -
Momentum Capsule Networks
Josef Gugglberger, Antonio Rodriguez-sanchez, David Peer, September 2022
[openreview] [pdf] [bib] -
ANCER: Anisotropic Certification via Sample-wise Volume Maximization
Francisco Eiras, Motasem Alfarra, Philip Torr, M. Pawan Kumar, Puneet K. Dokania, Bernard Ghanem, Adel Bibi, September 2022
[openreview] [pdf] [bib] [code] -
On the Choice of Interpolation Scheme for Neural CDEs
James Morrill, Patrick Kidger, Lingyi Yang, Terry Lyons, September 2022
[openreview] [pdf] [bib] -
Conformal Prediction Intervals with Temporal Dependence
Zhen Lin, Shubhendu Trivedi, Jimeng Sun, September 2022
[openreview] [pdf] [bib] [code] -
Meta-Learning Sparse Compression Networks
Jonathan Schwarz, Yee Whye Teh, September 2022
[openreview] [pdf] [bib] -
Estimating Potential Outcome Distributions with Collaborating Causal Networks
Tianhui Zhou, William E Carson IV, David Carlson, September 2022
[openreview] [pdf] [bib] [code] -
Sparse Coding with Multi-layer Decoders using Variance Regularization
Katrina Evtimova, Yann LeCun, August 2022
[openreview] [pdf] [bib] [code] -
Emergent Abilities of Large Language Models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus, August 2022
[openreview] [pdf] [bib]
Certifications: Survey -
Efficient CDF Approximations for Normalizing Flows
Chandramouli Shama Sastry, Andreas Lehrmann, Marcus A Brubaker, Alexander Radovic, August 2022
[openreview] [pdf] [bib] -
Unsupervised Dense Information Retrieval with Contrastive Learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, Edouard Grave, August 2022
[openreview] [pdf] [bib] [code] -
Equivariant Mesh Attention Networks
Sourya Basu, Jose Gallego-Posada, Francesco Viganò, James Rowbottom, Taco Cohen, August 2022
[openreview] [pdf] [bib] [code] -
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons
Fangshuo Liao, Anastasios Kyrillidis, August 2022
[openreview] [pdf] [bib] [code] -
CoCa: Contrastive Captioners are Image-Text Foundation Models
Jiahui Yu, Zirui Wang, Vijay Vasudevan, Legg Yeung, Mojtaba Seyedhosseini, Yonghui Wu, August 2022
[openreview] [pdf] [bib] -
Attentive Walk-Aggregating Graph Neural Networks
Mehmet F Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang, August 2022
[openreview] [pdf] [bib] [code] -
Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation
Miao Xiong, Shen Li, Wenjie Feng, Ailin Deng, Jihai Zhang, Bryan Hooi, August 2022
[openreview] [pdf] [bib] [code] -
Optimal Client Sampling for Federated Learning
Wenlin Chen, Samuel Horváth, Peter Richtárik, August 2022
[openreview] [pdf] [bib] [code] -
DR-DSGD: A Distributionally Robust Decentralized Learning Algorithm over Graphs
Chaouki Ben Issaid, Anis Elgabli, Mehdi Bennis, August 2022
[openreview] [pdf] [bib] -
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning
ZHUOWEI WANG, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long, August 2022
[openreview] [pdf] [bib] [code] -
SFP: State-free Priors for Exploration in Off-Policy Reinforcement Learning
Marco Bagatella, Sammy Joe Christen, Otmar Hilliges, August 2022
[openreview] [pdf] [bib] [code] -
Zero-Shot Learning with Common Sense Knowledge Graphs
Nihal V. Nayak, Stephen Bach, August 2022
[openreview] [pdf] [bib] [code] -
Causal Feature Selection via Orthogonal Search
Ashkan Soleymani, Anant Raj, Stefan Bauer, Bernhard Schölkopf, Michel Besserve, August 2022
[openreview] [pdf] [bib] [code] -
Finding and Fixing Spurious Patterns with Explanations
Gregory Plumb, Marco Tulio Ribeiro, Ameet Talwalkar, August 2022
[openreview] [pdf] [bib] [code] -
High Fidelity Visualization of What Your Self-Supervised Representation Knows About
Florian Bordes, Randall Balestriero, Pascal Vincent, August 2022
[openreview] [pdf] [bib] [code] -
The Fundamental Limits of Neural Networks for Interval Certified Robustness
Matthew B Mirman, Maximilian Baader, Martin Vechev, August 2022
[openreview] [pdf] [bib] -
TITRATED: Learned Human Driving Behavior without Infractions via Amortized Inference
Vasileios Lioutas, Adam Scibior, Frank Wood, August 2022
[openreview] [pdf] [bib] -
No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL
Han Wang, Archit Sakhadeo, Adam M White, James M Bell, Vincent Liu, Xutong Zhao, Puer Liu, Tadashi Kozuno, Alona Fyshe, Martha White, August 2022
[openreview] [pdf] [bib] -
Mean-Field Langevin Dynamics : Exponential Convergence and Annealing
Lénaïc Chizat, August 2022
[openreview] [pdf] [bib] [code] -
Variational Disentanglement for Domain Generalization
Yufei Wang, Haoliang Li, Hao Cheng, Bihan Wen, Lap-Pui Chau, Alex Kot, August 2022
[openreview] [pdf] [bib] -
On Robustness to Missing Video for Audiovisual Speech Recognition
Oscar Chang, Otavio Braga, Hank Liao, Dmitriy Serdyuk, Olivier Siohan, August 2022
[openreview] [pdf] [bib] -
Identifying Causal Structure in Dynamical Systems
Dominik Baumann, Friedrich Solowjow, Karl Henrik Johansson, Sebastian Trimpe, August 2022
[openreview] [pdf] [bib] [code] -
Understanding AdamW through Proximal Methods and Scale-Freeness
Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky, Francesco Orabona, August 2022
[openreview] [pdf] [bib] [code] -
Diagnosing and Fixing Manifold Overfitting in Deep Generative Models
Gabriel Loaiza-Ganem, Brendan Leigh Ross, Jesse C Cresswell, Anthony L. Caterini, August 2022
[openreview] [pdf] [bib] [code] -
Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions?
Anastasis Kratsios, Behnoosh Zamanlooy, August 2022
[openreview] [pdf] [bib] -
Recurrent networks, hidden states and beliefs in partially observable environments
Gaspard Lambrechts, Adrien Bolland, Damien Ernst, August 2022
[openreview] [pdf] [bib] -
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan O Arik, Chen-Yu Lee, Tomas Pfister, August 2022
[openreview] [pdf] [bib] -
A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey
Elahe Arani, Shruthi Gowda, Ratnajit Mukherjee, Omar Magdy, Senthilkumar Sockalingam Kathiresan, Bahram Zonooz, August 2022
[openreview] [pdf] [bib]
Certifications: Survey -
Domain-invariant Feature Exploration for Domain Generalization
Wang Lu, Jindong Wang, Haoliang Li, Yiqiang Chen, Xing Xie, August 2022
[openreview] [pdf] [bib] [code] -
Stable and Interpretable Unrolled Dictionary Learning
Bahareh Tolooshams, Demba E. Ba, August 2022
[openreview] [pdf] [bib] [code] -
Exploring Generative Neural Temporal Point Process
Haitao Lin, Lirong Wu, Guojiang Zhao, Liu Pai, Stan Z. Li, August 2022
[openreview] [pdf] [bib] [code] -
Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization
David Peer, Bart Keulen, Sebastian Stabinger, Justus Piater, Antonio Rodriguez-sanchez, August 2022
[openreview] [pdf] [bib] [code] -
Online Coresets for Parameteric and Non-Parametric Bregman Clustering
Supratim Shit, Anirban Dasgupta, Rachit Chhaya, Jayesh Choudhari, August 2022
[openreview] [pdf] [bib] -
Max-Affine Spline Insights Into Deep Network Pruning
Haoran You, Randall Balestriero, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, Shang Wu, Yingyan Lin, Richard Baraniuk, August 2022
[openreview] [pdf] [bib] -
Did I do that? Blame as a means to identify controlled effects in reinforcement learning
Oriol Corcoll, Youssef Sherif Mansour Mohamed, Raul Vicente, August 2022
[openreview] [pdf] [bib] -
QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning
Srivatsan Krishnan, Max Lam, Sharad Chitlangia, Zishen Wan, Gabriel Barth-maron, Aleksandra Faust, Vijay Janapa Reddi, July 2022
[openreview] [pdf] [bib] [code] -
NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes
Suhani Vora, Noha Radwan, Klaus Greff, Henning Meyer, Kyle Genova, Mehdi S. M. Sajjadi, Etienne Pot, Andrea Tagliasacchi, Daniel Duckworth, July 2022
[openreview] [pdf] [bib] [code] -
Learning to Switch Among Agents in a Team
Vahid Balazadeh Meresht, Abir De, Adish Singla, Manuel Gomez Rodriguez, July 2022
[openreview] [pdf] [bib] [code] -
A Self-Supervised Framework for Function Learning and Extrapolation
Simon Segert, Jonathan Cohen, July 2022
[openreview] [pdf] [bib] [code] -
Deep Classifiers with Label Noise Modeling and Distance Awareness
Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou, July 2022
[openreview] [pdf] [bib] [code] -
Ranking Recovery under Privacy Considerations
Minoh Jeong, Alex Dytso, Martina Cardone, July 2022
[openreview] [pdf] [bib] -
Learning the Transformer Kernel
Sankalan Pal Chowdhury, Adamos Solomou, Kumar Avinava Dubey, Mrinmaya Sachan, July 2022
[openreview] [pdf] [bib] [code] -
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks
David Alvarez-Melis, Yair Schiff, Youssef Mroueh, July 2022
[openreview] [pdf] [bib] [code] -
Deformation Robust Roto-Scale-Translation Equivariant CNNs
Liyao Gao, Guang Lin, Wei Zhu, July 2022
[openreview] [pdf] [bib] [code] -
On the link between conscious function and general intelligence in humans and machines
Arthur Juliani, Kai Arulkumaran, Shuntaro Sasai, Ryota Kanai, July 2022
[openreview] [pdf] [bib]
Certifications: Survey -
Non-Deterministic Behavior of Thompson Sampling with Linear Payoffs and How to Avoid It
Doruk Kilitcioglu, Serdar Kadioglu, July 2022
[openreview] [pdf] [bib] [code]
Certifications: Reproducibility -
Structural Learning in Artificial Neural Networks: A Neural Operator Perspective
Kaitlin Maile, Luga Hervé, Dennis George Wilson, July 2022
[openreview] [pdf] [bib]
Certifications: Survey -
Adversarial Feature Augmentation and Normalization for Visual Recognition
Tianlong Chen, Yu Cheng, Zhe Gan, Jianfeng Wang, Lijuan Wang, Jingjing Liu, Zhangyang Wang, July 2022
[openreview] [pdf] [bib] [code] -
Your Policy Regularizer is Secretly an Adversary
Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Gregoire Detetang, Markus Kunesch, Shane Legg, Pedro A Ortega, July 2022
[openreview] [pdf] [bib] -
How Expressive are Transformers in Spectral Domain for Graphs?
Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Hiroki Kanezashi, Toyotaro Suzumura, Isaiah Onando Mulang', July 2022
[openreview] [pdf] [bib] [code] -
Robust and Data-efficient Q-learning by Composite Value-estimation
Gabriel Kalweit, Maria Kalweit, Joschka Boedecker, July 2022
[openreview] [pdf] [bib] [code] -
Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation
Sanket Kamthe, So Takao, Shakir Mohamed, Marc Peter Deisenroth, July 2022
[openreview] [pdf] [bib] [code] -
The Graph Cut Kernel for Ranked Data
Michelangelo Conserva, Marc Peter Deisenroth, K S Sesh Kumar, July 2022
[openreview] [pdf] [bib] [code] -
NoiLin: Improving adversarial training and correcting stereotype of noisy labels
Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Lizhen Cui, Gang Niu, Masashi Sugiyama, June 2022
[openreview] [pdf] [bib] [code] -
Multi-Agent Off-Policy TDC with Near-Optimal Sample and Communication Complexities
Ziyi Chen, Yi Zhou, Rong-Rong Chen, June 2022
[openreview] [pdf] [bib] [code] -
Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress
Saket Gurukar, Priyesh Vijayan, srinivasan parthasarathy, Balaraman Ravindran, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel, June 2022
[openreview] [pdf] [bib] [code] -
Decoding EEG With Spiking Neural Networks on Neuromorphic Hardware
Neelesh Kumar, Guangzhi Tang, Raymond Yoo, Konstantinos P. Michmizos, June 2022
[openreview] [pdf] [bib] [code] -
Understanding Linearity of Cross-Lingual Word Embedding Mappings
Xutan Peng, Mark Stevenson, Chenghua Lin, Chen Li, June 2022
[openreview] [pdf] [bib] [code] -
TLDR: Twin Learning for Dimensionality Reduction
Yannis Kalantidis, Carlos Eduardo Rosar Kos Lassance, Jon Almazán, Diane Larlus, June 2022
[openreview] [pdf] [bib] [code] -
Clustering units in neural networks: upstream vs downstream information
Richard D Lange, David Rolnick, Konrad Kording, June 2022
[openreview] [pdf] [bib] [code] -
Boosting Search Engines with Interactive Agents
Leonard Adolphs, Benjamin Börschinger, Christian Buck, Michelle Chen Huebscher, Massimiliano Ciaramita, Lasse Espeholt, Thomas Hofmann, Yannic Kilcher, Sascha Rothe, Pier Giuseppe Sessa, Lierni Sestorain, June 2022
[openreview] [pdf] [bib] [code] -
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning
Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang, June 2022
[openreview] [pdf] [bib] [code]
Certifications: Featured -
Greedy Bayesian Posterior Approximation with Deep Ensembles
Aleksei Tiulpin, Matthew B. Blaschko, June 2022
[openreview] [pdf] [bib] [code] -
Auto-Lambda: Disentangling Dynamic Task Relationships
Shikun Liu, Stephen James, Andrew Davison, Edward Johns, June 2022
[openreview] [pdf] [bib] [code] -
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
Andreas Peter Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer, May 2022
[openreview] [pdf] [bib] [code]
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