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Accepted papers

• 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

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  [openreview] [pdf] [bib]

• GIT: A Generative Image-to-text Transformer for Vision and Language

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  [openreview] [pdf] [bib]

• Concave Utility Reinforcement Learning with Zero-Constraint Violations

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  [openreview] [pdf] [bib]

• Fast and Accurate Spreading Process Temporal Scale Estimation

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  [openreview] [pdf] [bib] [code]

• Extracting Local Reasoning Chains of Deep Neural Networks

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  [openreview] [pdf] [bib]

• On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces

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  [openreview] [pdf] [bib]

• Distribution Embedding Networks for Generalization from a Diverse Set of Classification Tasks

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  [openreview] [pdf] [bib]

• COIN++: Neural Compression Across Modalities

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  [openreview] [pdf] [bib] [code]

• Systematically and efficiently improving $k$-means initialization by pairwise-nearest-neighbor smoothing

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  [openreview] [pdf] [bib] [code]

• GhostSR: Learning Ghost Features for Efficient Image Super-Resolution

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  [openreview] [pdf] [bib] [code]

• DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents

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  [openreview] [pdf] [bib] [code]

• On the Origins of the Block Structure Phenomenon in Neural Network Representations

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  [openreview] [pdf] [bib]

• Interpretable Node Representation with Attribute Decoding

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  [openreview] [pdf] [bib]

• A Unified Domain Adaptation Framework with Distinctive Divergence Analysis

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  [openreview] [pdf] [bib]

• Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions

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  [openreview] [pdf] [bib]

• Counterfactual Learning with Multioutput Deep Kernels

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  [openreview] [pdf] [bib]

• Incorporating Sum Constraints into Multitask Gaussian Processes

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  [openreview] [pdf] [bib] [code]

• Degradation Attacks on Certifiably Robust Neural Networks

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  [openreview] [pdf] [bib] [code]

• If your data distribution shifts, use self-learning

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  [openreview] [pdf] [bib] [code]

• An approximate sampler for energy-based models with divergence diagnostics

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  [openreview] [pdf] [bib] [code]

• A Unified Survey on Anomaly, Novelty, Open-Set, and Out of-Distribution Detection: Solutions and Future Challenges

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  [openreview] [pdf] [bib] [code]

• Bayesian Methods for Constraint Inference in Reinforcement Learning

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]

• On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning

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  [openreview] [pdf] [bib]

• Reinventing Policy Iteration under Time Inconsistency

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  [openreview] [pdf] [bib] [code]

• Nonparametric Learning of Two-Layer ReLU Residual Units

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  [openreview] [pdf] [bib] [code]

• Stochastic Douglas-Rachford Splitting for Regularized Empirical Risk Minimization: Convergence, Mini-batch, and Implementation

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  [openreview] [pdf] [bib] [code]

• Does Entity Abstraction Help Generative Transformers Reason?

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  [openreview] [pdf] [bib]

• Complex-Valued Autoencoders for Object Discovery

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  [openreview] [pdf] [bib] [code]

• Learning Algorithms for Markovian Bandits:\\Is Posterior Sampling more Scalable than Optimism?

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  [openreview] [pdf] [bib] [code]

• Modeling Object Dissimilarity for Deep Saliency Prediction

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  [openreview] [pdf] [bib] [code]

• Optimizing Intermediate Representations of Generative Models for Phase Retrieval

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  [openreview] [pdf] [bib]

• Algorithms and Theory for Supervised Gradual Domain Adaptation

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  [openreview] [pdf] [bib]

• Teacher’s pet: understanding and mitigating biases in distillation

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  [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

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  [openreview] [pdf] [bib] [code]

• An Efficient One-Class SVM for Novelty Detection in IoT

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  [openreview] [pdf] [bib]

• Competition over data: how does data purchase affect users?

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  [openreview] [pdf] [bib] [code]

• Diffusion Models for Video Prediction and Infilling

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  [openreview] [pdf] [bib]

• Efficient Gradient Flows in Sliced-Wasserstein Space

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  [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

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  [openreview] [pdf] [bib]

• On the Paradox of Certified Training

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  [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

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  [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

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  [openreview] [pdf] [bib]

• Differentially Private Stochastic Expectation Propagation

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  [openreview] [pdf] [bib]

• Practicality of generalization guarantees for unsupervised domain adaptation with neural networks

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  [openreview] [pdf] [bib] [code]

• On Noise Abduction for Answering Counterfactual Queries: A Practical Outlook

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  [openreview] [pdf] [bib] [code]

• Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed

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  [openreview] [pdf] [bib]

• Bridging Offline and Online Experimentation: Constraint Active Search for Deployed Performance Optimization

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  [openreview] [pdf] [bib]

• Multi-Source Causal Inference Using Control Variates under Outcome Selection Bias

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  [openreview] [pdf] [bib]

• Identifiable Deep Generative Models via Sparse Decoding

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  [openreview] [pdf] [bib] [code]

• Using unsupervised learning to detect broken symmetries, with relevance to searches for parity violation in nature.

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  [openreview] [pdf] [bib] [code]

• Integrating Rankings into Quantized Scores in Peer Review

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  [openreview] [pdf] [bib]

• Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning

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  [openreview] [pdf] [bib] [code]

• Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning

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  [openreview] [pdf] [bib]

• Secure Domain Adaptation with Multiple Sources

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  [openreview] [pdf] [bib]

• Teaching Models to Express Their Uncertainty in Words

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  [openreview] [pdf] [bib] [code]

• On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning

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  [openreview] [pdf] [bib] [code]

• The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning

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  [openreview] [pdf] [bib]

• Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation

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  [openreview] [pdf] [bib]

• Centroids Matching: an efficient Continual Learning approach operating in the embedding space

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  [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

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  [openreview] [pdf] [bib] [code]

• Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach

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  [openreview] [pdf] [bib] [code]

• Generative Adversarial Neural Operators

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  [openreview] [pdf] [bib] [code]

• Lookback for Learning to Branch

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  [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

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  [openreview] [pdf] [bib] [code]

• Differentiable Model Compression via Pseudo Quantization Noise

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  [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

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  [openreview] [pdf] [bib] [code]

• DR-DSGD: A Distributionally Robust Decentralized Learning Algorithm over Graphs

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  [openreview] [pdf] [bib]

• SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning

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  [openreview] [pdf] [bib] [code]

• SFP: State-free Priors for Exploration in Off-Policy Reinforcement Learning

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  [openreview] [pdf] [bib] [code]

• Zero-Shot Learning with Common Sense Knowledge Graphs

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  [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

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  [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

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  [openreview] [pdf] [bib]

• TITRATED: Learned Human Driving Behavior without Infractions via Amortized Inference

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  [openreview] [pdf] [bib]

• No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL

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  [openreview] [pdf] [bib]

• Mean-Field Langevin Dynamics : Exponential Convergence and Annealing

  Lénaïc Chizat, August 2022
  [openreview] [pdf] [bib] [code]

• Variational Disentanglement for Domain Generalization

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  [openreview] [pdf] [bib]

• On Robustness to Missing Video for Audiovisual Speech Recognition

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  [openreview] [pdf] [bib]

• Identifying Causal Structure in Dynamical Systems

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  [openreview] [pdf] [bib] [code]

• Understanding AdamW through Proximal Methods and Scale-Freeness

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  [openreview] [pdf] [bib] [code]

• Diagnosing and Fixing Manifold Overfitting in Deep Generative Models

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  [openreview] [pdf] [bib] [code]

• Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions?

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  [openreview] [pdf] [bib]

• Recurrent networks, hidden states and beliefs in partially observable environments

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  [openreview] [pdf] [bib]

• Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection

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  [openreview] [pdf] [bib]

• A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey

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  [openreview] [pdf] [bib]
  Certifications: Survey

• Domain-invariant Feature Exploration for Domain Generalization

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  [openreview] [pdf] [bib] [code]

• Stable and Interpretable Unrolled Dictionary Learning

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  [openreview] [pdf] [bib] [code]

• Exploring Generative Neural Temporal Point Process

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  [openreview] [pdf] [bib] [code]

• Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization

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  [openreview] [pdf] [bib] [code]

• Online Coresets for Parameteric and Non-Parametric Bregman Clustering

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  [openreview] [pdf] [bib]

• Max-Affine Spline Insights Into Deep Network Pruning

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  [openreview] [pdf] [bib]

• Did I do that? Blame as a means to identify controlled effects in reinforcement learning

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  [openreview] [pdf] [bib]

• QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning

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  [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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