JMLR Volume 19

• Numerical Analysis near Singularities in RBF Networks

  Weili Guo, Haikun Wei, Yew-Soon Ong, Jaime Rubio Hervas, Junsheng Zhao, Hai Wang, Kanjian Zhang (1):1−39, 2018 PDF BibTeX

• A Two-Stage Penalized Least Squares Method for Constructing Large Systems of Structural Equations

  Chen Chen, Min Ren, Min Zhang, Dabao Zhang (2):1−34, 2018 PDF BibTeX

• Approximate Submodularity and its Applications: Subset Selection, Sparse Approximation and Dictionary Selection

  Abhimanyu Das, David Kempe (3):1−34, 2018 PDF BibTeX

• A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference

  Ahmed M. Alaa, Mihaela van der Schaar (4):1−62, 2018 PDF BibTeX

• Can We Trust the Bootstrap in High-dimensions? The Case of Linear Models

  Noureddine El Karoui, Elizabeth Purdom (5):1−66, 2018 PDF BibTeX

• RSG: Beating Subgradient Method without Smoothness and Strong Convexity

  Tianbao Yang, Qihang Lin (6):1−33, 2018 PDF BibTeX

• Patchwork Kriging for Large-scale Gaussian Process Regression

  Chiwoo Park, Daniel Apley (7):1−43, 2018 PDF BibTeX

• Scalable Bayes via Barycenter in Wasserstein Space

  Sanvesh Srivastava, Cheng Li, David B. Dunson (8):1−35, 2018 PDF BibTeX

• Experience Selection in Deep Reinforcement Learning for Control

  Tim de Bruin, Jens Kober, Karl Tuyls, Robert Babuška (9):1−56, 2018 PDF BibTeX

• A Constructive Approach to $L_0$ Penalized Regression

  Jian Huang, Yuling Jiao, Yanyan Liu, Xiliang Lu (10):1−37, 2018 PDF BibTeX

• Change-Point Computation for Large Graphical Models: A Scalable Algorithm for Gaussian Graphical Models with Change-Points

  Leland Bybee, Yves Atchadé (11):1−38, 2018 PDF BibTeX

• Statistical Analysis and Parameter Selection for Mapper

  Mathieu Carrière, Bertrand Michel, Steve Oudot (12):1−39, 2018 PDF BibTeX

• A Robust Learning Approach for Regression Models Based on Distributionally Robust Optimization

  Ruidi Chen, Ioannis Ch. Paschalidis (13):1−48, 2018 PDF BibTeX

• Model-Free Trajectory-based Policy Optimization with Monotonic Improvement

  Riad Akrour, Abbas Abdolmaleki, Hany Abdulsamad, Jan Peters, Gerhard Neumann (14):1−25, 2018 PDF BibTeX

• Regularized Optimal Transport and the Rot Mover's Distance

  Arnaud Dessein, Nicolas Papadakis, Jean-Luc Rouas (15):1−53, 2018 PDF BibTeX

• ELFI: Engine for Likelihood-Free Inference

  Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski (16):1−7, 2018 webpagecodePDF BibTeX

• Streaming kernel regression with provably adaptive mean, variance, and regularization

  Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau (17):1−34, 2018 PDF BibTeX

• Dual Principal Component Pursuit

  Manolis C. Tsakiris, René Vidal (18):1−50, 2018 PDF BibTeX

• Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters

  Yi Zhou, Yingbin Liang, Yaoliang Yu, Wei Dai, Eric P. Xing (19):1−32, 2018 PDF BibTeX

• Refining the Confidence Level for Optimistic Bandit Strategies

  Tor Lattimore (20):1−32, 2018 PDF BibTeX

• ThunderSVM: A Fast SVM Library on GPUs and CPUs

  Zeyi Wen, Jiashuai Shi, Qinbin Li, Bingsheng He, Jian Chen (21):1−5, 2018 webpagecodePDF BibTeX

• Robust Synthetic Control

  Muhammad Amjad, Devavrat Shah, Dennis Shen (22):1−51, 2018 PDF BibTeX

• Reverse Iterative Volume Sampling for Linear Regression

  Michał Dereziński, Manfred K. Warmuth (23):1−39, 2018 PDF BibTeX

• Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems

  Lyudmila Grigoryeva, Juan-Pablo Ortega (24):1−40, 2018 PDF BibTeX

• Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

  Maziar Raissi (25):1−24, 2018 PDF BibTeX

• OpenEnsembles: A Python Resource for Ensemble Clustering

  Tom Ronan, Shawn Anastasio, Zhijie Qi, Pedro Henrique S. Vieira Tavares, Roman Sloutsky, Kristen M. Naegle (26):1−6, 2018 webpagecodePDF BibTeX

• Importance Sampling for Minibatches

  Dominik Csiba, Peter Richtárik (27):1−21, 2018 PDF BibTeX

• Generalized Rank-Breaking: Computational and Statistical Tradeoffs

  Ashish Khetan, Sewoong Oh (28):1−42, 2018 PDF BibTeX

• Gradient Descent Learns Linear Dynamical Systems

  Moritz Hardt, Tengyu Ma, Benjamin Recht (29):1−44, 2018 PDF BibTeX

• Parallelizing Spectrally Regularized Kernel Algorithms

  Nicole Mücke, Gilles Blanchard (30):1−29, 2018 PDF BibTeX

• A Direct Approach for Sparse Quadratic Discriminant Analysis

  Binyan Jiang, Xiangyu Wang, Chenlei Leng (31):1−37, 2018 PDF BibTeX

• Distribution-Specific Hardness of Learning Neural Networks

  Ohad Shamir (32):1−29, 2018 PDF BibTeX

• Goodness-of-Fit Tests for Random Partitions via Symmetric Polynomials

  Chao Gao (33):1−50, 2018 PDF BibTeX

• A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms

  Bhavya Kailkhura, Jayaraman J. Thiagarajan, Charvi Rastogi, Pramod K. Varshney, Peer-Timo Bremer (34):1−46, 2018 PDF BibTeX

• Kernel Density Estimation for Dynamical Systems

  Hanyuan Hang, Ingo Steinwart, Yunlong Feng, Johan A.K. Suykens (35):1−49, 2018 PDF BibTeX

• Invariant Models for Causal Transfer Learning

  Mateo Rojas-Carulla, Bernhard Schölkopf, Richard Turner, Jonas Peters (36):1−34, 2018 PDF BibTeX

• The xyz algorithm for fast interaction search in high-dimensional data

  Gian-Andrea Thanei, Nicolai Meinshausen, Rajen D. Shah (37):1−42, 2018 PDF BibTeX

• Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning

  Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos (38):1−47, 2018 PDF BibTeX

• State-by-state Minimax Adaptive Estimation for Nonparametric Hidden {M}arkov Models

  Luc Lehéricy (39):1−46, 2018 PDF BibTeX

• Learning from Comparisons and Choices

  Sahand Negahban, Sewoong Oh, Kiran K. Thekumparampil, Jiaming Xu (40):1−95, 2018 PDF BibTeX

• Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models

  Bin Dai, Yu Wang, John Aston, Gang Hua, David Wipf (41):1−42, 2018 PDF BibTeX

• An Efficient and Effective Generic Agglomerative Hierarchical Clustering Approach

  Julien Ah-Pine (42):1−43, 2018 PDF BibTeX

• Markov Blanket and Markov Boundary of Multiple Variables

  Xu-Qing Liu, Xin-Sheng Liu (43):1−50, 2018 PDF BibTeX

• Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions

  Carl-Johann Simon-Gabriel, Bernhard Schölkopf (44):1−29, 2018 PDF BibTeX

• Random Forests, Decision Trees, and Categorical Predictors: The "Absent Levels" Problem

  Timothy C. Au (45):1−30, 2018 PDF BibTeX

• On Tight Bounds for the Lasso

  Sara van de Geer (46):1−48, 2018 PDF BibTeX

• Harmonic Mean Iteratively Reweighted Least Squares for Low-Rank Matrix Recovery

  Christian Kümmerle, Juliane Sigl (47):1−49, 2018 github.comPDF BibTeX

• On Generalized Bellman Equations and Temporal-Difference Learning

  Huizhen Yu, A. Rupam Mahmood, Richard S. Sutton (48):1−49, 2018 PDF BibTeX

• Design and Analysis of the NIPS 2016 Review Process

  Nihar B. Shah, Behzad Tabibian, Krikamol Muandet, Isabelle Guyon, Ulrike von Luxburg (49):1−34, 2018 PDF BibTeX

• Emergence of Invariance and Disentanglement in Deep Representations

  Alessandro Achille, Stefano Soatto (50):1−34, 2018 PDF BibTeX

• Covariances, Robustness, and Variational Bayes

  Ryan Giordano, Tamara Broderick, Michael I. Jordan (51):1−49, 2018 PDF BibTeX

• Accelerating Cross-Validation in Multinomial Logistic Regression with $\ell_1$-Regularization

  Tomoyuki Obuchi, Yoshiyuki Kabashima (52):1−30, 2018 PDF BibTeX

• Profile-Based Bandit with Unknown Profiles

  Sylvain Lamprier, Thibault Gisselbrecht, Patrick Gallinari (53):1−40, 2018 PDF BibTeX

• How Deep Are Deep Gaussian Processes?

  Matthew M. Dunlop, Mark A. Girolami, Andrew M. Stuart, Aretha L. Teckentrup (54):1−46, 2018 PDF BibTeX

• Fast MCMC Sampling Algorithms on Polytopes

  Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu (55):1−86, 2018 PDF BibTeX

• Modular Proximal Optimization for Multidimensional Total-Variation Regularization

  Alvaro Barbero, Suvrit Sra (56):1−82, 2018 PDF BibTeX

• On Semiparametric Exponential Family Graphical Models

  Zhuoran Yang, Yang Ning, Han Liu (57):1−59, 2018 PDF BibTeX

• Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor Classifier

  Alain Celisse, Tristan Mary-Huard (58):1−54, 2018 PDF BibTeX

• Maximum Selection and Sorting with Adversarial Comparators

  Jayadev Acharya, Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Ananda Theertha Suresh (59):1−31, 2018 PDF BibTeX

• A New and Flexible Approach to the Analysis of Paired Comparison Data

  Ivo F. D. Oliveira, Nir Ailon, Ori Davidov (60):1−29, 2018 PDF BibTeX

• Simple Classification Using Binary Data

  Deanna Needell, Rayan Saab, Tina Woolf (61):1−30, 2018 PDF BibTeX

• Hinge-Minimax Learner for the Ensemble of Hyperplanes

  Dolev Raviv, Tamir Hazan, Margarita Osadchy (62):1−30, 2018 PDF BibTeX

• Short-term Sparse Portfolio Optimization Based on Alternating Direction Method of Multipliers

  Zhao-Rong Lai, Pei-Yi Yang, Liangda Fang, Xiaotian Wu (63):1−28, 2018 codePDF BibTeX

• Scaling up Data Augmentation MCMC via Calibration

  Leo L. Duan, James E. Johndrow, David B. Dunson (64):1−34, 2018 PDF BibTeX

• Extrapolating Expected Accuracies for Large Multi-Class Problems

  Charles Zheng, Rakesh Achanta, Yuval Benjamini (65):1−30, 2018 PDF BibTeX

• Inference via Low-Dimensional Couplings

  Alessio Spantini, Daniele Bigoni, Youssef Marzouk (66):1−71, 2018 PDF BibTeX

• Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes

  Christian Donner, Manfred Opper (67):1−34, 2018 PDF BibTeX

• Multivariate Bayesian Structural Time Series Model

  Jinwen Qiu, S. Rao Jammalamadaka, Ning Ning (68):1−33, 2018 PDF BibTeX

• Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling

  Adrian Šošić, Elmar Rueckert, Jan Peters, Abdelhak M. Zoubir, Heinz Koeppl (69):1−45, 2018 PDF BibTeX

• The Implicit Bias of Gradient Descent on Separable Data

  Daniel Soudry, Elad Hoffer, Mor Shpigel Nacson, Suriya Gunasekar, Nathan Srebro (70):1−57, 2018 PDF BibTeX

• Optimal Quantum Sample Complexity of Learning Algorithms

  Srinivasan Arunachalam, Ronald de Wolf (71):1−36, 2018 PDF BibTeX

• Scikit-Multiflow: A Multi-output Streaming Framework

  Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem (72):1−5, 2018 codePDF BibTeX

• Optimal Bounds for Johnson-Lindenstrauss Transformations

  Michael Burr, Shuhong Gao, Fiona Knoll (73):1−22, 2018 PDF BibTeX

• An efficient distributed learning algorithm based on effective local functional approximations

  Dhruv Mahajan, Nikunj Agrawal, S. Sathiya Keerthi, Sundararajan Sellamanickam, Leon Bottou (74):1−37, 2018 PDF BibTeX

• Sparse Estimation in Ising Model via Penalized Monte Carlo Methods

  Blazej Miasojedow, Wojciech Rejchel (75):1−26, 2018 PDF BibTeX

• Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations

  Kai-Yang Chiang, Inderjit S. Dhillon, Cho-Jui Hsieh (76):1−35, 2018 PDF BibTeX

• A Note on Quickly Sampling a Sparse Matrix with Low Rank Expectation

  Karl Rohe, Jun Tao, Xintian Han, Norbert Binkiewicz (77):1−13, 2018 PDF BibTeX

• Online Bootstrap Confidence Intervals for the Stochastic Gradient Descent Estimator

  Yixin Fang, Jinfeng Xu, Lei Yang (78):1−21, 2018 PDF BibTeX

• A Random Matrix Analysis and Improvement of Semi-Supervised Learning for Large Dimensional Data

  Xiaoyi Mai (79):1−27, 2018 PDF BibTeX

• Robust PCA by Manifold Optimization

  Teng Zhang, Yi Yang (80):1−39, 2018 PDF BibTeX

• Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods

  Remi Leblond, Fabian Pedregosa, Simon Lacoste-Julien (81):1−68, 2018 PDF BibTeX

• Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling

  Mariano Tepper, Anirvan M. Sengupta, Dmitri Chklovskii (82):1−30, 2018 PDF BibTeX

• Seglearn: A Python Package for Learning Sequences and Time Series

  David M. Burns, Cari M. Whyne (83):1−7, 2018 codewebpagePDF BibTeX

• DALEX: Explainers for Complex Predictive Models in R

  Przemyslaw Biecek (84):1−5, 2018 PDF BibTeX