JMLR - volume 20 - 2019 论文列表 |
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Volume 20, 2019
Raaz Dwivedi Yuansi Chen Martin J. Wainwright Bin Yu
Model Selection in Bayesian Neural Networks via Horseshoe Priors.Soumya Ghosh Jiayu Yao Finale Doshi-Velez
Neural Empirical Bayes. DPPy: DPP Sampling with Python.Guillaume Gautier Guillermo Polito Rémi Bardenet Michal Valko
Differentiable reservoir computing.Lyudmila Grigoryeva Juan-Pablo Ortega
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning.Daniel Coelho de Castro Jeremy Tan Bernhard Kainz Ender Konukoglu Ben Glocker
All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously.Aaron Fisher Cynthia Rudin Francesca Dominici
New Convergence Aspects of Stochastic Gradient Algorithms.Lam M. Nguyen Phuong Ha Nguyen Peter Richtárik Katya Scheinberg Martin Takác Marten van Dijk
DataWig: Missing Value Imputation for Tables.Felix Bießmann Tammo Rukat Philipp Schmidt Prathik Naidu Sebastian Schelter Andrey Taptunov Dustin Lange David Salinas
Learning Overcomplete, Low Coherence Dictionaries with Linear Inference.Jesse A. Livezey Alejandro F. Bujan Friedrich T. Sommer
Fast Automatic Smoothing for Generalized Additive Models.Yousra El-Bachir Anthony C. Davison
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals.Andrew Cotter Heinrich Jiang Maya R. Gupta Serena Wang Taman Narayan Seungil You Karthik Sridharan
Shared Subspace Models for Multi-Group Covariance Estimation.Alexander M. Franks Peter Hoff
DBSCAN: Optimal Rates For Density-Based Cluster Estimation.Daren Wang Xinyang Lu Alessandro Rinaldo
Embarrassingly Parallel Inference for Gaussian Processes.Michael Minyi Zhang Sinead A. Williamson
Determinantal Point Processes for Coresets.Nicolas Tremblay Simon Barthelmé Pierre-Olivier Amblard
Stochastic Canonical Correlation Analysis.Chao Gao Dan Garber Nathan Srebro Jialei Wang Weiran Wang
Unsupervised Evaluation and Weighted Aggregation of Ranked Classification Predictions.Mehmet Eren Ahsen Robert M. Vogel Gustavo A. Stolovitzky
On the Convergence of Gaussian Belief Propagation with Nodes of Arbitrary Size.Francois Kamper Sarel Steel Johan A. du Preez
The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks. Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets.Jie Wang Zhanqiu Zhang Jieping Ye
A Kernel Multiple Change-point Algorithm via Model Selection.Sylvain Arlot Alain Celisse Zaïd Harchaoui
Sparse Kernel Regression with Coefficient-based $\ell_q-$regularization.Lei Shi Xiaolin Huang Yunlong Feng Johan A. K. Suykens
Learning by Unsupervised Nonlinear Diffusion.Mauro Maggioni James M. Murphy
Optimal Convergence Rates for Convex Distributed Optimization in Networks.Kevin Scaman Francis R. Bach Sébastien Bubeck Yin Tat Lee Laurent Massoulié
GraSPy: Graph Statistics in Python.Jaewon Chung Benjamin D. Pedigo Eric W. Bridgeford Bijan K. Varjavand Hayden S. Helm Joshua T. Vogelstein
Simultaneous Phase Retrieval and Blind Deconvolution via Convex Programming.Ali Ahmed Alireza Aghasi Paul Hand
SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition.Yuntao Chen Chenxia Han Yanghao Li Zehao Huang Yi Jiang Naiyan Wang Zhaoxiang Zhang
Quantifying Uncertainty in Online Regression Forests.Theodore Vasiloudis Gianmarco De Francisci Morales Henrik Boström
Convergence Guarantees for a Class of Non-convex and Non-smooth Optimization Problems.Koulik Khamaru Martin J. Wainwright
Approximation Algorithms for Stochastic Clustering.David G. Harris Shi Li Thomas W. Pensyl Aravind Srinivasan Khoa Trinh
High-dimensional Varying Index Coefficient Models via Stein's Identity.Sen Na Zhuoran Yang Zhaoran Wang Mladen Kolar
Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams.Vasileios Maroulas Joshua L. Mike Christopher Oballe
Learning Optimized Risk Scores. On Asymptotic and Finite-Time Optimality of Bayesian Predictors. Collective Matrix Completion. Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise.Niklas Pfister Sebastian Weichwald Peter Bühlmann Bernhard Schölkopf
Characterizing the Sample Complexity of Pure Private Learners.Amos Beimel Kobbi Nissim Uri Stemmer
Bayesian Optimization for Policy Search via Online-Offline Experimentation. Convergence of Gaussian Belief Propagation Under General Pairwise Factorization: Connecting Gaussian MRF with Pairwise Linear Gaussian Model. Minimal Sample Subspace Learning: Theory and Algorithms. Model-free Nonconvex Matrix Completion: Local Minima Analysis and Applications in Memory-efficient Kernel PCA. Provably Accurate Double-Sparse Coding.Thanh V. Nguyen Raymond K. W. Wong Chinmay Hegde
Nonparametric Bayesian Aggregation for Massive Data.Zuofeng Shang Botao Hao Guang Cheng
Decentralized Dictionary Learning Over Time-Varying Digraphs.Amir Daneshmand Ying Sun Gesualdo Scutari Francisco Facchinei Brian M. Sadler
Generalized Maximum Entropy Estimation.Tobias Sutter David Sutter Peyman Mohajerin Esfahani John Lygeros
Multiclass Boosting: Margins, Codewords, Losses, and Algorithms.Mohammad J. Saberian Nuno Vasconcelos
Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis.Nicolás García Trillos Daniel Sanz-Alonso Ruiyi Yang
Gaussian Processes with Linear Operator Inequality Constraints. Stochastic Variance-Reduced Cubic Regularization Methods.Dongruo Zhou Pan Xu Quanquan Gu
Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes.Luca Venturi Afonso S. Bandeira Joan Bruna
More Efficient Estimation for Logistic Regression with Optimal Subsamples. Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model.Sophie Burkhardt Stefan Kramer
Logical Explanations for Deep Relational Machines Using Relevance Information.Ashwin Srinivasan Lovekesh Vig Michael Bain
Time-to-Event Prediction with Neural Networks and Cox Regression.Håvard Kvamme Ørnulf Borgan Ida Scheel
Unsupervised Basis Function Adaptation for Reinforcement Learning. Causal Learning via Manifold Regularization.Steven M. Hill Chris J. Oates Duncan A. J. Blythe Sach Mukherjee
Learning Representations of Persistence Barcodes.Christoph D. Hofer Roland Kwitt Marc Niethammer
ORCA: A Matlab/Octave Toolbox for Ordinal Regression.Javier Sánchez-Monedero Pedro Antonio Gutiérrez María Pérez-Ortiz
Deep Exploration via Randomized Value Functions.Ian Osband Benjamin Van Roy Daniel J. Russo Zheng Wen
ADMMBO: Bayesian Optimization with Unknown Constraints using ADMM.Setareh Ariafar Jaume Coll-Font Dana H. Brooks Jennifer G. Dy
Approximate Profile Maximum Likelihood.Dmitri S. Pavlichin Jiantao Jiao Tsachy Weissman
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction.Bin Hong Weizhong Zhang Wei Liu Jieping Ye Deng Cai Xiaofei He Jie Wang
Ivanov-Regularised Least-Squares Estimators over Large RKHSs and Their Interpolation Spaces.Stephen Page Steffen Grünewälder
Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models.Kean Ming Tan Junwei Lu Tong Zhang Han Liu
Binarsity: a penalization for one-hot encoded features in linear supervised learning.Mokhtar Z. Alaya Simon Bussy Stéphane Gaïffas Agathe Guilloux
Generic Inference in Latent Gaussian Process Models.Edwin V. Bonilla Karl Krauth Amir Dezfouli
Graph Reduction with Spectral and Cut Guarantees. Learning Attribute Patterns in High-Dimensional Structured Latent Attribute Models. Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery.Richard Y. Zhang Somayeh Sojoudi Javad Lavaei
Distributed Inference for Linear Support Vector Machine.Xiaozhou Wang Zhuoyi Yang Xi Chen Weidong Liu
Measuring the Effects of Data Parallelism on Neural Network Training.Christopher J. Shallue Jaehoon Lee Joseph M. Antognini Jascha Sohl-Dickstein Roy Frostig George E. Dahl
An Efficient Two Step Algorithm for High Dimensional Change Point Regression Models Without Grid Search.Abhishek Kaul Venkata K. Jandhyala Stergios B. Fotopoulos
A Representer Theorem for Deep Neural Networks. Learning Unfaithful $K$-separable Gaussian Graphical Models. Maximum Likelihood for Gaussian Process Classification and Generalized Linear Mixed Models under Case-Control Sampling.Omer Weissbrod Shachar Kaufman David Golan Saharon Rosset
Scalable Interpretable Multi-Response Regression via SEED.Zemin Zheng Mohammad Taha Bahadori Yan Liu Jinchi Lv
Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method.Ziyan Luo Defeng Sun Kim-Chuan Toh Naihua Xiu
Optimal Transport: Fast Probabilistic Approximation with Exact Solvers.Max Sommerfeld Jörn Schrieber Yoav Zemel Axel Munk
Complete Search for Feature Selection in Decision Trees. Regularization via Mass Transportation.Soroosh Shafieezadeh-Abadeh Daniel Kuhn Peyman Mohajerin Esfahani
Non-Convex Matrix Completion and Related Problems via Strong Duality.Maria-Florina Balcan Yingyu Liang Zhao Song David P. Woodruff Hongyang Zhang
Low Permutation-rank Matrices: Structural Properties and Noisy Completion.Nihar B. Shah Sivaraman Balakrishnan Martin J. Wainwright
Hamiltonian Monte Carlo with Energy Conserving Subsampling.Khue-Dung Dang Matias Quiroz Robert Kohn Minh-Ngoc Tran Mattias Villani
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction.William Herlands Daniel B. Neill Hannes Nickisch Andrew Gordon Wilson
Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data. Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion.Lijun Zhang Tianbao Yang Rong Jin Zhi-Hua Zhou
PyOD: A Python Toolbox for Scalable Outlier Detection.Yue Zhao Zain Nasrullah Zheng Li
High-Dimensional Poisson Structural Equation Model Learning via $\ell_1$-Regularized Regression. Simultaneous Private Learning of Multiple Concepts.Mark Bun Kobbi Nissim Uri Stemmer
iNNvestigate Neural Networks!Maximilian Alber Sebastian Lapuschkin Philipp Seegerer Miriam Hägele Kristof T. Schütt Grégoire Montavon Wojciech Samek Klaus-Robert Müller Sven Dähne Pieter-Jan Kindermans
AffectiveTweets: a Weka Package for Analyzing Affect in Tweets.Felipe Bravo-Marquez Eibe Frank Bernhard Pfahringer Saif M. Mohammad
Best Arm Identification for Contaminated Bandits.Jason Altschuler Victor-Emmanuel Brunel Alan Malek
A Particle-Based Variational Approach to Bayesian Non-negative Matrix Factorization.Muhammad A. Masood Finale Doshi-Velez
Dependent relevance determination for smooth and structured sparse regression.Anqi Wu Oluwasanmi Koyejo Jonathan W. Pillow
Model Selection via the VC Dimension.Merlin Mpoudeu Bertrand S. Clarke
An asymptotic analysis of distributed nonparametric methods. Streaming Principal Component Analysis From Incomplete Data.Armin Eftekhari Gregory Ongie Laura Balzano Michael B. Wakin
Bayesian Space-Time Partitioning by Sampling and Pruning Spanning Trees.Leonardo Vilela Teixeira Renato M. Assunção Rosangela Helena Loschi
Differentiable Game Mechanics.Alistair Letcher David Balduzzi Sébastien Racanière James Martens Jakob N. Foerster Karl Tuyls Thore Graepel
On the optimality of the Hedge algorithm in the stochastic regime.Jaouad Mourtada Stéphane Gaïffas
SMART: An Open Source Data Labeling Platform for Supervised Learning.Rob Chew Michael Wenger Caroline Kery Jason Nance Keith Richards Emily Hadley Peter Baumgartner
Tight Lower Bounds on the VC-dimension of Geometric Set Systems.Mónika Csikós Nabil H. Mustafa Andrey Kupavskii
Learning to Match via Inverse Optimal Transport.Ruilin Li Xiaojing Ye Haomin Zhou Hongyuan Zha
Quantification Under Prior Probability Shift: the Ratio Estimator and its Extensions.Afonso Fernandes Vaz Rafael Izbicki Rafael Bassi Stern
Prediction Risk for the Horseshoe Regression.Anindya Bhadra Jyotishka Datta Yunfan Li Nicholas G. Polson Brandon T. Willard
Nonuniformity of P-values Can Occur Early in Diverging Dimensions.Yingying Fan Emre Demirkaya Jinchi Lv
Generalized Score Matching for Non-Negative Data.Shiqing Yu Mathias Drton Ali Shojaie
Fairness Constraints: A Flexible Approach for Fair Classification.Muhammad Bilal Zafar Isabel Valera Manuel Gomez-Rodriguez Krishna P. Gummadi
Deep Optimal Stopping.Sebastian Becker Patrick Cheridito Arnulf Jentzen
Analysis of Langevin Monte Carlo via Convex Optimization.Alain Durmus Szymon Majewski Blazej Miasojedow
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning.Can Karakus Yifan Sun Suhas N. Diggavi Wotao Yin
Lazifying Conditional Gradient Algorithms.Gábor Braun Sebastian Pokutta Daniel Zink
Semi-Analytic Resampling in Lasso.Tomoyuki Obuchi Yoshiyuki Kabashima
On Consistent Vertex Nomination Schemes.Vince Lyzinski Keith Levin Carey E. Priebe
Variance-based Regularization with Convex Objectives.John C. Duchi Hongseok Namkoong
Learnability of Solutions to Conjunctive Queries. Proximal Distance Algorithms: Theory and Practice.Kevin L. Keys Hua Zhou Kenneth Lange
Active Learning for Cost-Sensitive Classification.Akshay Krishnamurthy Alekh Agarwal Tzu-Kuo Huang Hal Daumé III John Langford
A Representer Theorem for Deep Kernel Learning.Bastian Bohn Christian Rieger Michael Griebel
Nearly-tight VC-dimension and Pseudodimension Bounds for Piecewise Linear Neural Networks.Peter L. Bartlett Nick Harvey Christopher Liaw Abbas Mehrabian
Multi-scale Online Learning: Theory and Applications to Online Auctions and Pricing.Sébastien Bubeck Nikhil R. Devanur Zhiyi Huang Rad Niazadeh
The Sup-norm Perturbation of HOSVD and Low Rank Tensor Denoising. Robust Estimation of Derivatives Using Locally Weighted Least Absolute Deviation Regression.Wenwu Wang Ping Yu Lu Lin Tiejun Tong
Kernel Approximation Methods for Speech Recognition.Avner May Alireza Bagheri Garakani Zhiyun Lu Dong Guo Kuan Liu Aurélien Bellet Linxi Fan Michael Collins Daniel Hsu Brian Kingsbury Michael Picheny Fei Sha
The Common-directions Method for Regularized Empirical Risk Minimization.Po-Wei Wang Ching-Pei Lee Chih-Jen Lin
Multi-class Heterogeneous Domain Adaptation.Joey Tianyi Zhou Ivor W. Tsang Sinno Jialin Pan Mingkui Tan
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices. Neural Architecture Search: A Survey.Thomas Elsken Jan Hendrik Metzen Frank Hutter
Deep Reinforcement Learning for Swarm Systems.Maximilian Hüttenrauch Adrian Sosic Gerhard Neumann
Tunability: Importance of Hyperparameters of Machine Learning Algorithms.Philipp Probst Anne-Laure Boulesteix Bernd Bischl
Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems.Sondre Glimsdal Ole-Christoffer Granmo
Bayesian Combination of Probabilistic Classifiers using Multivariate Normal Mixtures. No-Regret Bayesian Optimization with Unknown Hyperparameters.Felix Berkenkamp Angela P. Schoellig Andreas Krause
Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots.Akshara Rai Rika Antonova Franziska Meier Christopher G. Atkeson
Efficient augmentation and relaxation learning for individualized treatment rules using observational data.Ying-Qi Zhao Eric B. Laber Yang Ning Sumona Saha Bruce E. Sands
Analysis of spectral clustering algorithms for community detection: the general bipartite setting. Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping.Shao-Bo Lin Yunwen Lei Ding-Xuan Zhou
Robust Frequent Directions with Application in Online Learning.Luo Luo Cheng Chen Zhihua Zhang Wu-Jun Li Tong Zhang
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python.Jason Ge Xingguo Li Haoming Jiang Han Liu Tong Zhang Mengdi Wang Tuo Zhao
DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization.Lin Xiao Adams Wei Yu Qihang Lin Weizhu Chen
Utilizing Second Order Information in Minibatch Stochastic Variance Reduced Proximal Iterations. Decontamination of Mutual Contamination Models.Julian Katz-Samuels Gilles Blanchard Clayton Scott
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations.Qianxiao Li Cheng Tai Weinan E
A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication.Miles E. Lopes Shusen Wang Michael W. Mahoney
Approximation Hardness for A Class of Sparse Optimization Problems.Yichen Chen Yinyu Ye Mengdi Wang
A Well-Tempered Landscape for Non-convex Robust Subspace Recovery.Tyler Maunu Teng Zhang Gilad Lerman
A New Approach to Laplacian Solvers and Flow Problems.Patrick Rebeschini Sekhar Tatikonda
Optimal Policies for Observing Time Series and Related Restless Bandit Problems.Christopher R. Dance Tomi Silander
Matched Bipartite Block Model with Covariates.Zahra S. Razaee Arash A. Amini Jingyi Jessica Li
The Relationship Between Agnostic Selective Classification, Active Learning and the Disagreement Coefficient. NetSDM: Semantic Data Mining with Network Analysis.Jan Kralj Marko Robnik-Sikonja Nada Lavrac
Kernels for Sequentially Ordered Data.Franz J. Király Harald Oberhauser
Exact Clustering of Weighted Graphs via Semidefinite Programming. Iterated Learning in Dynamic Social Networks. Pyro: Deep Universal Probabilistic Programming.Eli Bingham Jonathan P. Chen Martin Jankowiak Fritz Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman
Monotone Learning with Rectified Wire Networks.Veit Elser Dan Schmidt Jonathan S. Yedidia
TensorLy: Tensor Learning in Python.Jean Kossaifi Yannis Panagakis Anima Anandkumar Maja Pantic
Group Invariance, Stability to Deformations, and Complexity of Deep Convolutional Representations. Joint PLDA for Simultaneous Modeling of Two Factors.Luciana Ferrer Mitchell McLaren
Determining the Number of Latent Factors in Statistical Multi-Relational Learning.Chengchun Shi Wenbin Lu Rui Song
Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics.Yanning Shen Tianyi Chen Georgios B. Giannakis
Spectrum Estimation from a Few Entries. Accelerated Alternating Projections for Robust Principal Component Analysis.HanQin Cai Jian-Feng Cai Ke Wei
spark-crowd: A Spark Package for Learning from Crowdsourced Big Data.Enrique González Rodrigo Juan A. Aledo José A. Gámez
Multiplicative local linear hazard estimation and best one-sided cross-validation.María Luz Gámiz Pérez María Dolores Martínez Miranda Jens Perch Nielsen
Delay and Cooperation in Nonstochastic Bandits.Nicolò Cesa-Bianchi Claudio Gentile Yishay Mansour
Smooth neighborhood recommender systems.Ben Dai Junhui Wang Xiaotong Shen Annie Qu
Automated Scalable Bayesian Inference via Hilbert Coresets.Trevor Campbell Tamara Broderick
Approximations of the Restless Bandit Problem.Steffen Grünewälder Azadeh Khaleghi
Train and Test Tightness of LP Relaxations in Structured Prediction.Ofer Meshi Ben London Adrian Weller David A. Sontag
Scalable Kernel K-Means Clustering with Nystr\"om Approximation: Relative-Error Bounds.Shusen Wang Alex Gittens Michael W. Mahoney
An Approach to One-Bit Compressed Sensing Based on Probably Approximately Correct Learning Theory.Mehmet Eren Ahsen Mathukumalli Vidyasagar
Graphical Lasso and Thresholding: Equivalence and Closed-form Solutions. Dynamic Pricing in High-dimensions.Adel Javanmard Hamid Nazerzadeh
Forward-Backward Selection with Early Dropping.Giorgos Borboudakis Ioannis Tsamardinos
Scalable Approximations for Generalized Linear Problems.Murat A. Erdogdu Mohsen Bayati Lee H. Dicker
scikit-multilearn: A Python library for Multi-Label Classification.Piotr Szymanski Tomasz Kajdanowicz
Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression.Han Chen Garvesh Raskutti Ming Yuan
Convergence Rate of a Simulated Annealing Algorithm with Noisy Observations. Parsimonious Online Learning with Kernels via Sparse Projections in Function Space. Transport Analysis of Infinitely Deep Neural Network. Adaptation Based on Generalized Discrepancy.