JMLR - volume 22 - 2021 论文列表 |
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Volume 22, 2021
Nikola Kovachki Samuel Lanthaler Siddhartha Mishra
VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning.
Luisa M. Zintgraf Sebastian Schulze Cong Lu Leo Feng Maximilian Igl Kyriacos Shiarlis Yarin Gal Katja Hofmann Shimon Whiteson
A Theory of the Risk for Optimization with Relaxation and its Application to Support Vector Machines. V-statistics and Variance Estimation.Zhengze Zhou Lucas Mentch Giles Hooker
An Online Sequential Test for Qualitative Treatment Effects.Chengchun Shi Shikai Luo Hongtu Zhu Rui Song
Double Generative Adversarial Networks for Conditional Independence Testing.Chengchun Shi Tianlin Xu Wicher Bergsma Lexin Li
Linear Bandits on Uniformly Convex Sets.Thomas Kerdreux Christophe Roux Alexandre d'Aspremont Sebastian Pokutta
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders.Oskar Allerbo Rebecka Jörnsten
LDLE: Low Distortion Local Eigenmaps.Dhruv Kohli Alexander Cloninger Gal Mishne
Contrastive Estimation Reveals Topic Posterior Information to Linear Models.Christopher Tosh Akshay Krishnamurthy Daniel Hsu
Graph Matching with Partially-Correct Seeds.Liren Yu Jiaming Xu Xiaojun Lin
Fast Learning for Renewal Optimization in Online Task Scheduling. Multilevel Monte Carlo Variational Inference. Gaussian Approximation for Bias Reduction in Q-Learning.Carlo D'Eramo Andrea Cini Alessandro Nuara Matteo Pirotta Cesare Alippi Jan Peters Marcello Restelli
Estimating the Lasso's Effective Noise. Partial Policy Iteration for L1-Robust Markov Decision Processes.Chin Pang Ho Marek Petrik Wolfram Wiesemann
Simultaneous Change Point Inference and Structure Recovery for High Dimensional Gaussian Graphical Models.Bin Liu Xinsheng Zhang Yufeng Liu
On the Hardness of Robust Classification.Pascale Gourdeau Varun Kanade Marta Kwiatkowska James Worrell
Transferability of Spectral Graph Convolutional Neural Networks.Ron Levie Wei Huang Lorenzo Bucci Michael M. Bronstein Gitta Kutyniok
Nonparametric Continuous Sensor Registration.William Clark Maani Ghaffari Anthony M. Bloch
Further results on latent discourse models and word embeddings.Sammy Khalife Douglas Soares Gonçalves Youssef Allouah Leo Liberti
CAT: Compression-Aware Training for bandwidth reduction.Chaim Baskin Brian Chmiel Evgenii Zheltonozhskii Ron Banner Alex M. Bronstein Avi Mendelson
Stable-Baselines3: Reliable Reinforcement Learning Implementations.Antonin Raffin Ashley Hill Adam Gleave Anssi Kanervisto Maximilian Ernestus Noah Dormann
Reproducing kernel Hilbert C*-module and kernel mean embeddings.Yuka Hashimoto Isao Ishikawa Masahiro Ikeda Fuyuta Komura Takeshi Katsura Yoshinobu Kawahara
Learning Bayesian Networks from Ordinal Data.Xiang Ge Luo Giusi Moffa Jack Kuipers
Exact Asymptotics for Linear Quadratic Adaptive Control. Regularized spectral methods for clustering signed networks.Mihai Cucuringu Apoorv Vikram Singh Déborah Sulem Hemant Tyagi
On the Stability Properties and the Optimization Landscape of Training Problems with Squared Loss for Neural Networks and General Nonlinear Conic Approximation Schemes. Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning.Chong Liu Yuqing Zhu Kamalika Chaudhuri Yu-Xiang Wang
Domain adaptation under structural causal models. Learning Strategies in Decentralized Matching Markets under Uncertain Preferences. ROOTS: Object-Centric Representation and Rendering of 3D Scenes.Chang Chen Fei Deng Sungjin Ahn
Optimized Score Transformation for Consistent Fair Classification.Dennis Wei Karthikeyan Natesan Ramamurthy Flávio du Pin Calmon
Estimating Uncertainty Intervals from Collaborating Networks.Tianhui Zhou Yitong Li Yuan Wu David E. Carlson
Model Linkage Selection for Cooperative Learning.Jiaying Zhou Jie Ding Kean Ming Tan Vahid Tarokh
Adversarial Monte Carlo Meta-Learning of Optimal Prediction Procedures.Alex Luedtke Incheoul Chung Oleg Sofrygin
Inference for the Case Probability in High-dimensional Logistic Regression.Zijian Guo Prabrisha Rakshit Daniel S. Herman Jinbo Chen
Bifurcation Spiking Neural Network.Shao-Qun Zhang Zhao-Yu Zhang Zhi-Hua Zhou
Batch greedy maximization of non-submodular functions: Guarantees and applications to experimental design.Jayanth Jagalur-Mohan Youssef M. Marzouk
Tractable Approximate Gaussian Inference for Bayesian Neural Networks.James-A. Goulet Luong Ha Nguyen Saeid Amiri
Bayesian time-aligned factor analysis of paired multivariate time series.Arkaprava Roy Jana Schaich Borg David B. Dunson
On the Riemannian Search for Eigenvector Computation. Statistically and Computationally Efficient Change Point Localization in Regression Settings.Daren Wang Zifeng Zhao Kevin Z. Lin Rebecca Willett
Statistical Guarantees for Local Spectral Clustering on Random Neighborhood Graphs.Alden Green Sivaraman Balakrishnan Ryan J. Tibshirani
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals.Emilie Kaufmann Wouter M. Koolen
On lp-hyperparameter Learning via Bilevel Nonsmooth Optimization.Takayuki Okuno Akiko Takeda Akihiro Kawana Motokazu Watanabe
Consistency of Gaussian Process Regression in Metric Spaces. Quasi-Monte Carlo Quasi-Newton in Variational Bayes. Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations.Jesús María Sanz-Serna Konstantinos C. Zygalakis
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks.Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste
DIG: A Turnkey Library for Diving into Graph Deep Learning Research.Meng Liu Youzhi Luo Limei Wang Yaochen Xie Hao Yuan Shurui Gui Haiyang Yu Zhao Xu Jingtun Zhang Yi Liu Keqiang Yan Haoran Liu Cong Fu Bora Oztekin Xuan Zhang Shuiwang Ji
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo.Mert Gürbüzbalaban Xuefeng Gao Yuanhan Hu Lingjiong Zhu
DeEPCA: Decentralized Exact PCA with Linear Convergence Rate. Consensus-Based Optimization on the Sphere: Convergence to Global Minimizers and Machine Learning.Massimo Fornasier Lorenzo Pareschi Hui Huang Philippe Sünnen
Expanding Boundaries of Gap Safe Screening.Cássio Fraga Dantas Emmanuel Soubies Cédric Févotte
GIBBON: General-purpose Information-Based Bayesian Optimisation.Henry B. Moss David S. Leslie Javier Gonzalez Paul Rayson
A general linear-time inference method for Gaussian Processes on one dimension.Jackson Loper David M. Blei John P. Cunningham Liam Paninski
A Generalised Linear Model Framework for β-Variational Autoencoders based on Exponential Dispersion Families.Robert Sicks Ralf Korn Stefanie Schwaar
Probabilistic Iterative Methods for Linear Systems.Jon Cockayne Ilse C. F. Ipsen Chris J. Oates Tim W. Reid
sklvq: Scikit Learning Vector Quantization.Rick van Veen Michael Biehl Gert-Jan de Vries
Learning with semi-definite programming: statistical bounds based on fixed point analysis and excess risk curvature.Stéphane Chrétien Mihai Cucuringu Guillaume Lecué Lucie Neirac
Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be.Valerio Biscione Jeffrey S. Bowers
How Well Generative Adversarial Networks Learn Distributions. Tighter Risk Certificates for Neural Networks.María Pérez-Ortiz Omar Risvaplata John Shawe-Taylor Csaba Szepesvári
FATE: An Industrial Grade Platform for Collaborative Learning With Data Protection.Yang Liu Tao Fan Tianjian Chen Qian Xu Qiang Yang
Representer Theorems in Banach Spaces: Minimum Norm Interpolation, Regularized Learning and Semi-Discrete Inverse Problems. Bayesian Distance Clustering. Stochastic Online Optimization using Kalman Recursion.Joseph De Vilmarest Olivier Wintenberger
Classification vs regression in overparameterized regimes: Does the loss function matter?Vidya Muthukumar Adhyyan Narang Vignesh Subramanian Mikhail Belkin Daniel Hsu Anant Sahai
A Bayes-Optimal View on Adversarial Examples. Shape-Enforcing Operators for Generic Point and Interval Estimators of Functions.Xi Chen Victor Chernozhukov Iván Fernández-Val Scott Kostyshak Ye Luo
Soft Tensor Regression.Georgia Papadogeorgou Zhengwu Zhang David B. Dunson
Thompson Sampling Algorithms for Cascading Bandits.Zixin Zhong Wang Chi Chueng Vincent Y. F. Tan
A Unified Framework for Spectral Clustering in Sparse Graphs.Lorenzo Dall'Amico Romain Couillet Nicolas Tremblay
Context-dependent Networks in Multivariate Time Series: Models, Methods, and Risk Bounds in High Dimensions.Lili Zheng Garvesh Raskutti Rebecca Willett Benjamin Mark
TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads.Pawel Rosciszewski Michal Martyniak Filip Schodowski
dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python.Hubert Baniecki Wojciech Kretowicz Piotr Piatyszek Jakub Wisniewski Przemyslaw Biecek
Cooperative SGD: A Unified Framework for the Design and Analysis of Local-Update SGD Algorithms. Convex Geometry and Duality of Over-parameterized Neural Networks. Bandit Learning in Decentralized Matching Markets.Lydia T. Liu Feng Ruan Horia Mania Michael I. Jordan
Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks.Amin Rakhsha Goran Radanovic Rati Devidze Xiaojin Zhu Adish Singla
Explaining by Removing: A Unified Framework for Model Explanation.Ian Covert Scott M. Lundberg Su-In Lee
Oblivious Data for Fairness with Kernels.Steffen Grünewälder Azadeh Khaleghi
A Unified Convergence Analysis for Shuffling-Type Gradient Methods.Lam M. Nguyen Quoc Tran-Dinh Dzung T. Phan Phuong Ha Nguyen Marten van Dijk
Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls.Jeongho Kim Jaeuk Shin Insoon Yang
Langevin Monte Carlo: random coordinate descent and variance reduction. Failures of Model-dependent Generalization Bounds for Least-norm Interpolation.Peter L. Bartlett Philip M. Long
Learning partial correlation graphs and graphical models by covariance queries.Gábor Lugosi Jakub Truszkowski Vasiliki Velona Piotr Zwiernik
Interpretable Deep Generative Recommendation Models.Huafeng Liu Liping Jing Jingxuan Wen Pengyu Xu Jiaqi Wang Jian Yu Michael K. Ng
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMap, and PaCMAP for Data Visualization.Yingfan Wang Haiyang Huang Cynthia Rudin Yaron Shaposhnik
Refined approachability algorithms and application to regret minimization with global costs. On ADMM in Deep Learning: Convergence and Saturation-Avoidance.Jinshan Zeng Shao-Bo Lin Yuan Yao Ding-Xuan Zhou
Integrated Principal Components Analysis.Tiffany M. Tang Genevera I. Allen
Particle-Gibbs Sampling for Bayesian Feature Allocation Models.Alexandre Bouchard-Côté Andrew Roth
COKE: Communication-Censored Decentralized Kernel Learning.Ping Xu Yue Wang Xiang Chen Zhi Tian
Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation.Pierre Humbert Batiste Le Bars Laurent Oudre Argyris Kalogeratos Nicolas Vayatis
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings.Keith D. Levin Fred Roosta Minh Tang Michael W. Mahoney Carey E. Priebe
Sparse Popularity Adjusted Stochastic Block Model.Majid Noroozi Marianna Pensky Ramchandra Rimal
Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models.Fei Wang Ling Zhou Lu Tang Peter X. K. Song
On the Estimation of Network Complexity: Dimension of Graphons. Collusion Detection and Ground Truth Inference in Crowdsourcing for Labeling Tasks.Changyue Song Kaibo Liu Xi Zhang
One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them.Saber Salehkaleybar Arsalan Sharif-Nassab S. Jamaloddin Golestani
Differentially Private Regression and Classification with Sparse Gaussian Processes.Michael Thomas Smith Mauricio A. Álvarez Neil D. Lawrence
Matrix Product States for Inference in Discrete Probabilistic Models.Rasmus Bonnevie Mikkel N. Schmidt
As You Like It: Localization via Paired Comparisons.Andrew K. Massimino Mark A. Davenport
Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions.HanQin Cai Keaton Hamm Longxiu Huang Deanna Needell
mlr3pipelines - Flexible Machine Learning Pipelines in R.Martin Binder Florian Pfisterer Michel Lang Lennart Schneider Lars Kotthoff Bernd Bischl
Benchmarking Unsupervised Object Representations for Video Sequences.Marissa A. Weis Kashyap Chitta Yash Sharma Wieland Brendel Matthias Bethge Andreas Geiger Alexander S. Ecker
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning.Pascal Klink Hany Abdulsamad Boris Belousov Carlo D'Eramo Jan Peters Joni Pajarinen
Alibi Explain: Algorithms for Explaining Machine Learning Models.Janis Klaise Arnaud Van Looveren Giovanni Vacanti Alexandru Coca
Improved Shrinkage Prediction under a Spiked Covariance Structure.Trambak Banerjee Gourab Mukherjee Debashis Paul
A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration.Yuetian Luo Garvesh Raskutti Ming Yuan Anru R. Zhang
Conditional independences and causal relations implied by sets of equations.Tineke Blom Mirthe M. van Diepen Joris M. Mooij
Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond.Xin Bing Florentina Bunea Seth Strimas-Mackey Marten H. Wegkamp
Locally Private k-Means Clustering. Doubly infinite residual neural networks: a diffusion process approach.Stefano Peluchetti Stefano Favaro
Achieving Fairness in the Stochastic Multi-Armed Bandit Problem.Vishakha Patil Ganesh Ghalme Vineet Nair Y. Narahari
Replica Exchange for Non-Convex Optimization. Unlinked Monotone Regression.Fadoua Balabdaoui Charles R. Doss Cécile Durot
Optimal Rates of Distributed Regression with Imperfect Kernels. Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity.Bin Gu Xiyuan Wei Shangqian Gao Ziran Xiong Cheng Deng Heng Huang
First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems.Mingrui Liu Hassan Rafique Qihang Lin Tianbao Yang
Asymptotic Normality, Concentration, and Coverage of Generalized Posteriors. Estimation and Optimization of Composite Outcomes.Daniel J. Luckett Eric B. Laber Siyeon Kim Michael R. Kosorok
The ensmallen library for flexible numerical optimization.Ryan R. Curtin Marcus Edel Rahul Ganesh Prabhu Suryoday Basak Zhihao Lou Conrad Sanderson
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning.Charles H. Martin Michael W. Mahoney
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program).Joelle Pineau Philippe Vincent-Lamarre Koustuv Sinha Vincent Larivière Alina Beygelzimer Florence d'Alché-Buc Emily B. Fox Hugo Larochelle
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review.Ivan Stelmakh Nihar B. Shah Aarti Singh
Counterfactual Mean Embeddings.Krikamol Muandet Motonobu Kanagawa Sorawit Saengkyongam Sanparith Marukatat
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning.Tim van Erven Wouter M. Koolen Dirk van der Hoeven
Are We Forgetting about Compositional Optimisers in Bayesian Optimisation?Antoine Grosnit Alexander Imani Cowen-Rivers Rasul Tutunov Ryan-Rhys Griffiths Jun Wang Haitham Bou-Ammar
When Does Gradient Descent with Logistic Loss Find Interpolating Two-Layer Networks?Niladri S. Chatterji Philip M. Long Peter L. Bartlett
Information criteria for non-normalized models.Takeru Matsuda Masatoshi Uehara Aapo Hyvärinen
The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks.Takuo Matsubara Chris J. Oates François-Xavier Briol
A Greedy Algorithm for Quantizing Neural Networks. What Causes the Test Error? Going Beyond Bias-Variance via ANOVA. Kernel Smoothing, Mean Shift, and Their Learning Theory with Directional Data. Factorization Machines with Regularization for Sparse Feature Interactions.Kyohei Atarashi Satoshi Oyama Masahito Kurihara
Hardness of Identity Testing for Restricted Boltzmann Machines and Potts models.Antonio Blanca Zongchen Chen Daniel Stefankovic Eric Vigoda
Universal consistency and rates of convergence of multiclass prototype algorithms in metric spaces. Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent. Hyperparameter Optimization via Sequential Uniform Designs. Statistical guarantees for local graph clustering.Wooseok Ha Kimon Fountoulakis Michael W. Mahoney
Optimal Minimax Variable Selection for Large-Scale Matrix Linear Regression Model.Meiling Hao Lianqiang Qu Dehan Kong Liuquan Sun Hongtu Zhu
Nonparametric Modeling of Higher-Order Interactions via Hypergraphons. On efficient multilevel Clustering via Wasserstein distances.Viet Huynh Nhat Ho Nhan Dam XuanLong Nguyen Mikhail Yurochkin Hung Bui Dinh Q. Phung
Individual Fairness in Hindsight. Non-attracting Regions of Local Minima in Deep and Wide Neural Networks.Henning Petzka Cristian Sminchisescu
Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace.Jesús Arroyo Avanti Athreya Joshua Cape Guodong Chen Carey E. Priebe Joshua T. Vogelstein
Pseudo-Marginal Hamiltonian Monte Carlo.Johan Alenlöv Arnoud Doucet Fredrik Lindsten
Generalization Properties of hyper-RKHS and its Applications.Fanghui Liu Lei Shi Xiaolin Huang Jie Yang Johan A. K. Suykens
Hoeffding's Inequality for General Markov Chains and Its Applications to Statistical Learning.Jianqing Fan Bai Jiang Qiang Sun
An algorithmic view of L2 regularization and some path-following algorithms. Hybrid Predictive Models: When an Interpretable Model Collaborates with a Black-box Model. Implicit Langevin Algorithms for Sampling From Log-concave Densities.Liam Hodgkinson Robert Salomone Fred Roosta
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives.Antoine Dedieu Hussein Hazimeh Rahul Mazumder
An Inertial Newton Algorithm for Deep Learning.Camille Castera Jérôme Bolte Cédric Févotte Edouard Pauwels
A Contextual Bandit Bake-off.Alberto Bietti Alekh Agarwal John Langford
Locally Differentially-Private Randomized Response for Discrete Distribution Learning.Adriano Pastore Michael Gastpar
MushroomRL: Simplifying Reinforcement Learning Research.Carlo D'Eramo Davide Tateo Andrea Bonarini Marcello Restelli Jan Peters
Learning Whenever Learning is Possible: Universal Learning under General Stochastic Processes. Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime.Niladri S. Chatterji Philip M. Long
Optimal Bounds between f-Divergences and Integral Probability Metrics. LassoNet: A Neural Network with Feature Sparsity.Ismael Lemhadri Feng Ruan Louis Abraham Robert Tibshirani
Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints.Molei Liu Yin Xia Kelly Cho Tianxi Cai
Bandit Convex Optimization in Non-stationary Environments.Peng Zhao Guanghui Wang Lijun Zhang Zhi-Hua Zhou
A flexible model-free prediction-based framework for feature ranking.Jingyi Jessica Li Yiling Elaine Chen Xin Tong
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness.George Wynne François-Xavier Briol Mark Girolami
Sparse Convex Optimization via Adaptively Regularized Hard Thresholding.Kyriakos Axiotis Maxim Sviridenko
Langevin Dynamics for Adaptive Inverse Reinforcement Learning of Stochastic Gradient Algorithms.Vikram Krishnamurthy George Yin
Empirical Bayes Matrix Factorization. Some Theoretical Insights into Wasserstein GANs.Gérard Biau Maxime Sangnier Ugo Tanielian
A General Framework for Adversarial Label Learning. Strong Consistency, Graph Laplacians, and the Stochastic Block Model.Shaofeng Deng Shuyang Ling Thomas Strohmer
An Importance Weighted Feature Selection Stability Measure. Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization. NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization.Ali Ramezani-Kebrya Fartash Faghri Ilya Markov Vitalii Aksenov Dan Alistarh Daniel M. Roy
A Lyapunov Analysis of Accelerated Methods in Optimization.Ashia C. Wilson Ben Recht Michael I. Jordan
L-SVRG and L-Katyusha with Arbitrary Sampling.Xun Qian Zheng Qu Peter Richtárik
Non-parametric Quantile Regression via the K-NN Fused Lasso.Steven Siwei Ye Oscar Hernan Madrid Padilla
River: machine learning for streaming data in Python.Jacob Montiel Max Halford Saulo Martiello Mastelini Geoffrey Bolmier Raphaël Sourty Robin Vaysse Adil Zouitine Heitor Murilo Gomes Jesse Read Talel Abdessalem Albert Bifet
mvlearn: Multiview Machine Learning in Python.Ronan Perry Gavin Mischler Richard Guo Theo Lee Alexander Chang Arman Koul Cameron Franz Hugo Richard Iain Carmichael Pierre Ablin Alexandre Gramfort Joshua T. Vogelstein
Towards a Unified Analysis of Random Fourier Features.Zhu Li Jean-Francois Ton Dino Oglic Dino Sejdinovic
Beyond English-Centric Multilingual Machine Translation.Angela Fan Shruti Bhosale Holger Schwenk Zhiyi Ma Ahmed El-Kishky Siddharth Goyal Mandeep Baines Onur Celebi Guillaume Wenzek Vishrav Chaudhary Naman Goyal Tom Birch Vitaliy Liptchinsky Sergey Edunov Michael Auli Armand Joulin
Online stochastic gradient descent on non-convex losses from high-dimensional inference.Gérard Ben Arous Reza Gheissari Aukosh Jagannath
Pathwise Conditioning of Gaussian Processes.James T. Wilson Viacheslav Borovitskiy Alexander Terenin Peter Mostowsky Marc Peter Deisenroth
Explaining Explanations: Axiomatic Feature Interactions for Deep Networks.Joseph D. Janizek Pascal Sturmfels Su-In Lee
A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints.Guodong Zhang Xuchan Bao Laurent Lessard Roger B. Grosse
Learning a High-dimensional Linear Structural Equation Model via l1-Regularized Regression.Gunwoong Park Sang Jun Moon Sion Park Jong-June Jeon
LocalGAN: Modeling Local Distributions for Adversarial Response Generation.Baoxun Wang Zhen Xu Huan Zhang Kexin Qiu Deyuan Zhang Chengjie Sun
OpenML-Python: an extensible Python API for OpenML.Matthias Feurer Jan N. van Rijn Arlind Kadra Pieter Gijsbers Neeratyoy Mallik Sahithya Ravi Andreas Müller Joaquin Vanschoren Frank Hutter
Adaptive estimation of nonparametric functionals.Lin Liu Rajarshi Mukherjee James M. Robins Eric Tchetgen Tchetgen
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift.Alekh Agarwal Sham M. Kakade Jason D. Lee Gaurav Mahajan
Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach.Alberto Maria Metelli Matteo Pirotta Daniele Calandriello Marcello Restelli
Guided Visual Exploration of Relations in Data Sets.Kai Puolamäki Emilia Oikarinen Andreas Henelius
Histogram Transform Ensembles for Large-scale Regression.Hanyuan Hang Zhouchen Lin Xiaoyu Liu Hongwei Wen
Consistent Semi-Supervised Graph Regularization for High Dimensional Data. Flexible Signal Denoising via Flexible Empirical Bayes Shrinkage.Zhengrong Xing Peter Carbonetto Matthew Stephens
NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation.Anastasis Kratsios Cody B. Hyndman
Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler.Tingting Zhao Alexandre Bouchard-Côté
Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs.Tomer Galanti Sagie Benaim Lior Wolf
Bayesian Text Classification and Summarization via A Class-Specified Topic Model.Feifei Wang Junni L. Zhang Yichao Li Ke Deng Jun S. Liu
Edge Sampling Using Local Network Information. On Solving Probabilistic Linear Diophantine Equations.Patrick Kreitzberg Oliver Serang
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis.Andreas C. Damianou Neil D. Lawrence Carl Henrik Ek
Gradient Methods Never Overfit On Separable Data. Variance Reduced Median-of-Means Estimator for Byzantine-Robust Distributed Inference.Jiyuan Tu Weidong Liu Xiaojun Mao Xi Chen
Statistical Query Lower Bounds for Tensor PCA. PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings.Mehdi Ali Max Berrendorf Charles Tapley Hoyt Laurent Vermue Sahand Sharifzadeh Volker Tresp Jens Lehmann
Knowing what You Know: valid and validated confidence sets in multiclass and multilabel prediction.Maxime Cauchois Suyash Gupta John C. Duchi
Communication-Efficient Distributed Covariance Sketch, with Application to Distributed PCA.Zengfeng Huang Xuemin Lin Wenjie Zhang Ying Zhang
Is SGD a Bayesian sampler? Well, almost.Chris Mingard Guillermo Valle Pérez Joar Skalse Ard A. Louis
POT: Python Optimal Transport.Rémi Flamary Nicolas Courty Alexandre Gramfort Mokhtar Z. Alaya Aurélie Boisbunon Stanislas Chambon Laetitia Chapel Adrien Corenflos Kilian Fatras Nemo Fournier Léo Gautheron Nathalie T. H. Gayraud Hicham Janati Alain Rakotomamonjy Ievgen Redko Antoine Rolet Antony Schutz Vivien Seguy Danica J. Sutherland Romain Tavenard Alexander Tong Titouan Vayer
ChainerRL: A Deep Reinforcement Learning Library.Yasuhiro Fujita Prabhat Nagarajan Toshiki Kataoka Takahiro Ishikawa
Analyzing the discrepancy principle for kernelized spectral filter learning algorithms. Attention is Turing-Complete.Jorge Pérez Pablo Barceló Javier Marinkovic
Kernel Operations on the GPU, with Autodiff, without Memory Overflows.Benjamin Charlier Jean Feydy Joan Alexis Glaunès François-David Collin Ghislain Durif
Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives.Michael Muehlebach Michael I. Jordan
Prediction against a limited adversary.Erhan Bayraktar Ibrahim Ekren Xin Zhang
Phase Diagram for Two-layer ReLU Neural Networks at Infinite-width Limit.Tao Luo Zhi-Qin John Xu Zheng Ma Yaoyu Zhang
Testing Conditional Independence via Quantile Regression Based Partial Copulas.Lasse Petersen Niels Richard Hansen
Determining the Number of Communities in Degree-corrected Stochastic Block Models.Shujie Ma Liangjun Su Yichong Zhang
Path Length Bounds for Gradient Descent and Flow.Chirag Gupta Sivaraman Balakrishnan Aaditya Ramdas
A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family.Trambak Banerjee Qiang Liu Gourab Mukherjee Wengunag Sun
Approximate Newton Methods.Haishan Ye Luo Luo Zhihua Zhang
Dynamic Tensor Recommender Systems.Yanqing Zhang Xuan Bi Niansheng Tang Annie Qu
Sparse Tensor Additive Regression.Botao Hao Boxiang Wang Pengyuan Wang Jingfei Zhang Jian Yang Will Wei Sun
Geometric structure of graph Laplacian embeddings.Nicolás García Trillos Franca Hoffmann Bamdad Hosseini
How to Gain on Power: Novel Conditional Independence Tests Based on Short Expansion of Conditional Mutual Information.Mariusz Kubkowski Jan Mielniczuk Pawel Teisseyre
Stochastic Proximal AUC Maximization. A Distributed Method for Fitting Laplacian Regularized Stratified Models.Jonathan Tuck Shane T. Barratt Stephen P. Boyd
Predictive Learning on Hidden Tree-Structured Ising Models.Konstantinos E. Nikolakakis Dionysios S. Kalogerias Anand D. Sarwate
Estimation and Inference for High Dimensional Generalized Linear Models: A Splitting and Smoothing Approach. Normalizing Flows for Probabilistic Modeling and Inference.George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende Shakir Mohamed Balaji Lakshminarayanan
Incorporating Unlabeled Data into Distributionally Robust Learning.Charlie Frogner Sebastian Claici Edward Chien Justin Solomon
Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data. GemBag: Group Estimation of Multiple Bayesian Graphical Models.Xinming Yang Lingrui Gan Naveen N. Narisetty Feng Liang
Subspace Clustering through Sub-Clusters.Weiwei Li Jan Hannig Sayan Mukherjee
Sparse and Smooth Signal Estimation: Convexification of L0-Formulations.Alper Atamtürk Andrés Gómez Shaoning Han
Projection-free Decentralized Online Learning for Submodular Maximization over Time-Varying Networks.Junlong Zhu Qingtao Wu Mingchuan Zhang Ruijuan Zheng Keqin Li
Structure Learning of Undirected Graphical Models for Count Data.Nguyen Thi Kim Hue Monica Chiogna
From Low Probability to High Confidence in Stochastic Convex Optimization.Damek Davis Dmitriy Drusvyatskiy Lin Xiao Junyu Zhang
Optimal Feedback Law Recovery by Gradient-Augmented Sparse Polynomial Regression.Behzad Azmi Dante Kalise Karl Kunisch
Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory. Optimal Structured Principal Subspace Estimation: Metric Entropy and Minimax Rates.T. Tony Cai Hongzhe Li Rong Ma
RaSE: Random Subspace Ensemble Classification. Wasserstein barycenters can be computed in polynomial time in fixed dimension.Jason M. Altschuler Enric Boix-Adserà
Banach Space Representer Theorems for Neural Networks and Ridge Splines. High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm.Wenlong Mou Yi-An Ma Martin J. Wainwright Peter L. Bartlett Michael I. Jordan
From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction.Henning Lange Steven L. Brunton J. Nathan Kutz
Residual Energy-Based Models for Text.Anton Bakhtin Yuntian Deng Sam Gross Myle Ott Marc'Aurelio Ranzato Arthur Szlam
giotto-tda: : A Topological Data Analysis Toolkit for Machine Learning and Data Exploration.Guillaume Tauzin Umberto Lupo Lewis Tunstall Julian Burella Pérez Matteo Caorsi Anibal M. Medina-Mardones Alberto Dassatti Kathryn Hess
Risk-Averse Learning by Temporal Difference Methods with Markov Risk Measures. A Bayesian Contiguous Partitioning Method for Learning Clustered Latent Variables.Zhao Tang Luo Huiyan Sang Bani K. Mallick
Multi-class Gaussian Process Classification with Noisy Inputs.Carlos Villacampa-Calvo Bryan Zaldivar Eduardo C. Garrido-Merchán Daniel Hernández-Lobato
Learning and Planning for Time-Varying MDPs Using Maximum Likelihood Estimation. Neighborhood Structure Assisted Non-negative Matrix Factorization and Its Application in Unsupervised Point-wise Anomaly Detection.Imtiaz Ahmed Xia Ben Hu Mithun P. Acharya Yu Ding
Asynchronous Online Testing of Multiple Hypotheses.Tijana Zrnic Aaditya Ramdas Michael I. Jordan
Learning interaction kernels in heterogeneous systems of agents from multiple trajectories.Fei Lu Mauro Maggioni Sui Tang
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference.Tianyu Wang Marco Morucci M. Usaid Awan Yameng Liu Sudeepa Roy Cynthia Rudin Alexander Volfovsky
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms.Oliver Kroemer Scott Niekum George Konidaris
Single and Multiple Change-Point Detection with Differential Privacy.Wanrong Zhang Sara Krehbiel Rui Tuo Yajun Mei Rachel Cummings
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits. Inference In High-dimensional Single-Index Models Under Symmetric Designs.Hamid Eftekhari Moulinath Banerjee Yaacov Ritov
Finite Time LTI System Identification.Tuhin Sarkar Alexander Rakhlin Munther A. Dahleh
Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions. Entangled Kernels - Beyond Separability. A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems.Giulio Galvan Matteo Lapucci Chih-Jen Lin Marco Sciandrone
When random initializations help: a study of variational inference for community detection.Purnamrita Sarkar Y. X. Rachel Wang Soumendu Sundar Mukherjee
A Fast Globally Linearly Convergent Algorithm for the Computation of Wasserstein Barycenters.Lei Yang Jia Li Defeng Sun Kim-Chuan Toh
Aggregated Hold-Out.Guillaume Maillard Sylvain Arlot Matthieu Lerasle
Ranking and synchronization from pairwise measurements via SVD.Alexandre d'Aspremont Mihai Cucuringu Hemant Tyagi
A Unified Sample Selection Framework for Output Noise Filtering: An Error-Bound Perspective.Gaoxia Jiang Wenjian Wang Yuhua Qian Jiye Liang
Continuous Time Analysis of Momentum Methods.Nikola B. Kovachki Andrew M. Stuart
Pykg2vec: A Python Library for Knowledge Graph Embedding.Shih-Yuan Yu Sujit Rokka Chhetri Arquimedes Canedo Palash Goyal Mohammad Abdullah Al Faruque
Simple and Fast Algorithms for Interactive Machine Learning with Random Counter-examples. On Multi-Armed Bandit Designs for Dose-Finding Trials.Maryam Aziz Emilie Kaufmann Marie-Karelle Riviere
Homogeneity Structure Learning in Large-scale Panel Data with Heavy-tailed Errors. Global and Quadratic Convergence of Newton Hard-Thresholding Pursuit.Shenglong Zhou Naihua Xiu Hou-Duo Qi
Unfolding-Model-Based Visualization: Theory, Method and Applications.Yunxiao Chen Zhiliang Ying Haoran Zhang
Mixing Time of Metropolis-Hastings for Bayesian Community Detection. Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm.Defeng Sun Kim-Chuan Toh Yancheng Yuan
A Unified Framework for Random Forest Prediction Error Estimation. Preference-based Online Learning with Dueling Bandits: A Survey.Viktor Bengs Róbert Busa-Fekete Adil El Mesaoudi-Paul Eyke Hüllermeier
Consistent estimation of small masses in feature sampling.Fadhel Ayed Marco Battiston Federico Camerlenghi Stefano Favaro
The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models.Carlos Alberto Gomez-Uribe Brian Karrer
An Empirical Study of Bayesian Optimization: Acquisition Versus Partition.Erich Merrill Alan Fern Xiaoli Z. Fern Nima Dolatnia
Regulating Greed Over Time in Multi-Armed Bandits.Stefano Tracà Cynthia Rudin Weiyu Yan
Domain Generalization by Marginal Transfer Learning.Gilles Blanchard Aniket Anand Deshmukh Ürün Dogan Gyemin Lee Clayton Scott
On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests.