[edit]
[edit]
Editors: Amos Storkey, Fernando Perez-Cruz
Filter Authors: Filter Titles:
The Geometry of Random Features
; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1-9
Gauged Mini-Bucket Elimination for Approximate Inference
Sungsoo Ahn, Michael Chertkov, Jinwoo Shin, Adrian Weller; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:10-19
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians
Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:20-28
An Analysis of Categorical Distributional Reinforcement Learning
Mark Rowland, Marc Bellemare, Will Dabney, Remi Munos, Yee Whye Teh; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:29-37
Combinatorial Preconditioners for Proximal Algorithms on Graphs
Thomas Möllenhoff, Zhenzhang Ye, Tao Wu, Daniel Cremers; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:38-47
[abs][Download PDF]
Growth-Optimal Portfolio Selection under CVaR Constraints
Guy Uziel, Ran El-Yaniv; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:48-57
Accelerated Stochastic Power Iteration
Peng Xu, Bryan He, Christopher De Sa, Ioannis Mitliagkas, Chris Re; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:58-67
Multi-scale Nystrom Method
Woosang Lim, Rundong Du, Bo Dai, Kyomin Jung, Le Song, Haesun Park; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:68-76
Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach
Satoshi Hara, Kohei Hayashi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:77-85
Mixed Membership Word Embeddings for Computational Social Science
James Foulds; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:86-95
Fast Threshold Tests for Detecting Discrimination
Emma Pierson, Sam Corbett-Davies, Sharad Goel; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:96-105
Iterative Supervised Principal Components
Juho Piironen, Aki Vehtari; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:106-114
Iterative Spectral Method for Alternative Clustering
Chieh Wu, Stratis Ioannidis, Mario Sznaier, Xiangyu Li, David Kaeli, Jennifer Dy; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:115-123
Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means
Dennis Forster, Jörg Lücke; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:124-132
Parallelised Bayesian Optimisation via Thompson Sampling
Kirthevasan Kandasamy, Akshay Krishnamurthy, Jeff Schneider, Barnabas Poczos; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:133-142
On the challenges of learning with inference networks on sparse, high-dimensional data
Rahul Krishnan, Dawen Liang, Matthew Hoffman; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:143-151
Post Selection Inference with Kernels
Makoto Yamada, Yuta Umezu, Kenji Fukumizu, Ichiro Takeuchi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:152-160
On how complexity affects the stability of a predictor
Joel Ratsaby; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:161-167
[abs][Download PDF]
On Truly Block Eigensolvers via Riemannian Optimization
Zhiqiang Xu, Xin Gao; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:168-177
Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond
Heng Guo, Kaan Kara, Ce Zhang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:178-187
IHT dies hard: Provable accelerated Iterative Hard Thresholding
Rajiv Khanna, Anastasios Kyrillidis; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:188-198
[abs][Download PDF]
Finding Global Optima in Nonconvex Stochastic Semidefinite Optimization with Variance Reduction
Jinshan Zeng, Ke Ma, Yuan Yao; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:199-207
Outlier Detection and Robust Estimation in Nonparametric Regression
Dehan Kong, Howard Bondell, Weining Shen; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:208-216
[abs][Download PDF]
Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis
Luca Ambrogioni, Eric Maris; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:217-225
[abs][Download PDF]
AdaGeo: Adaptive Geometric Learning for Optimization and Sampling
Gabriele Abbati, Alessandra Tosi, Michael Osborne, Seth Flaxman; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:226-234
Online Learning with Non-Convex Losses and Non-Stationary Regret
Xiand Gao, Xiaobo Li, Shuzhong Zhang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:235-243
Learning Determinantal Point Processes in Sublinear Time
Christophe Dupuy, Francis Bach; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:244-257
Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding
Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:258-268
Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis
Hiroyuki Kasai, Hiroyuki Sato, Bamdev Mishra; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:269-278
Online Boosting Algorithms for Multi-label Ranking
Young Hun Jung, Ambuj Tewari; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:279-287
Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications
Sijia Liu, Jie Chen, Pin-Yu Chen, Alfred Hero; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:288-297
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups
Paul Rolland, Jonathan Scarlett, Ilija Bogunovic, Volkan Cevher; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:298-307
Robust Active Label Correction
Jan Kremer, Fei Sha, Christian Igel; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:308-316
Factorial HMMs with Collapsed Gibbs Sampling for Optimizing Long-term HIV Therapy
Amit Gruber, Chen Yanover, Tal El-Hay, Anders Sönnerborg, Vanni Borghi, Francesca Incardona, Yaara Goldschmidt; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:317-326
Optimal Submodular Extensions for Marginal Estimation
Pankaj Pansari, Chris Russell, M Pawan Kumar; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:327-335
Semi-Supervised Learning with Competitive Infection Models
Nir Rosenfeld, Amir Globerson; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:336-346
Discriminative Learning of Prediction Intervals
Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:347-355
Topic Compositional Neural Language Model
Wenlin Wang, Zhe Gan, Wenqi Wang, Dinghan Shen, Jiaji Huang, Wei Ping, Sanjeev Satheesh, Lawrence Carin; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:356-365
Learning Priors for Invariance
Eric Nalisnick, Padhraic Smyth; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:366-375
[abs][Download PDF]
Optimal Cooperative Inference
Scott Cheng-Hsin Yang, Yue Yu, arash Givchi, Pei Wang, Wai Keen Vong, Patrick Shafto; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:376-385
Stochastic Multi-armed Bandits in Constant Space
David Liau, Zhao Song, Eric Price, Ger Yang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:386-394
Matrix completability analysis via graph k-connectivity
Dehua Cheng, Natali Ruchansky, Yan Liu; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:395-403
FLAG n’ FLARE: Fast Linearly-Coupled Adaptive Gradient Methods
Xiang Cheng, Fred Roosta, Stefan Palombo, Peter Bartlett, Michael Mahoney; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:404-414
Multi-view Metric Learning in Vector-valued Kernel Spaces
Riikka Huusari, Hachem Kadri, Cécile Capponi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:415-424
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
William Herlands, Edward McFowland, Andrew Wilson, Daniel Neill; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:425-434
Dropout as a Low-Rank Regularizer for Matrix Factorization
Jacopo Cavazza, Pietro Morerio, Benjamin Haeffele, Connor Lane, Vittorio Murino, Rene Vidal; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:435-444
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer
Tianbao Yang, Zhe Li, Lijun Zhang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:445-453
[abs][Download PDF]
Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables
Masaaki Takada, Taiji Suzuki, Hironori Fujisawa; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:454-463
Boosting Variational Inference: an Optimization Perspective
Francesco Locatello, Rajiv Khanna, Joydeep Ghosh, Gunnar Ratsch; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:464-472
Personalized and Private Peer-to-Peer Machine Learning
Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki, Marc Tommasi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:473-481
Tensor Regression Meets Gaussian Processes
Rose Yu, Guangyu Li, Yan Liu; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:482-490
A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization
Emanuel Laude, Tao Wu, Daniel Cremers; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:491-499
Medoids in Almost-Linear Time via Multi-Armed Bandits
Vivek Bagaria, Govinda Kamath, Vasilis Ntranos, Martin Zhang, David Tse; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:500-509
Regional Multi-Armed Bandits
Zhiyang Wang, Ruida Zhou, Cong Shen; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:510-518
Nearly second-order optimality of online joint detection and estimation via one-sample update schemes
Yang Cao, Liyan Xie, Yao Xie, Huan Xu; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:519-528
Sum-Product-Quotient Networks
Or Sharir, Amnon Shashua; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:529-537
Exploiting Strategy-Space Diversity for Batch Bayesian Optimization
Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:538-547
Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods
Stephan Clémençon, François Portier; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:548-556
Group Invariance Principles for Causal Generative Models
Michel Besserve, Naji Shajarisales, Bernhard Schölkopf, Dominik Janzing; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:557-565
A Provable Algorithm for Learning Interpretable Scoring Systems
Nataliya Sokolovska, Yann Chevaleyre, Jean-Daniel Zucker; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:566-574
[abs][Download PDF]
Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes
Hyunjik Kim, Yee Whye Teh; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:575-584
Efficient Bandit Combinatorial Optimization Algorithm with Zero-suppressed Binary Decision Diagrams
Shinsaku Sakaue, Masakazu Ishihata, Shin-ichi Minato; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:585-594
Transfer Learning on fMRI Datasets
Hejia Zhang, Po-Hsuan Chen, Peter Ramadge; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:595-603
An Optimization Approach to Learning Falling Rule Lists
Chaofan Chen, Cynthia Rudin; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:604-612
Catalyst for Gradient-based Nonconvex Optimization
Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaid Harchaoui; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:613-622
[abs][Download PDF]
Benefits from Superposed Hawkes Processes
Hongteng Xu, Dixin Luo, Xu Chen, Lawrence Carin; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:623-631
[abs][Download PDF]
Nonparametric Preference Completion
Julian Katz-Samuels, Clayton Scott; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:632-641
Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training
Mathieu Sinn, Ambrish Rawat; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:642-651
Efficient and principled score estimation with Nyström kernel exponential families
Danica J. Sutherland, Heiko Strathmann, Michael Arbel, Arthur Gretton; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:652-660
Symmetric Variational Autoencoder and Connections to Adversarial Learning
Liqun Chen, Shuyang Dai, Yunchen Pu, Erjin Zhou, Chunyuan Li, Qinliang Su, Changyou Chen, Lawrence Carin; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:661-669
Few-shot Generative Modelling with Generative Matching Networks
Sergey Bartunov, Dmitry Vetrov; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:670-678
Nonlinear Weighted Finite Automata
Tianyu Li, Guillaume Rabusseau, Doina Precup; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:679-688
[abs][Download PDF]
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models
Hugh Salimbeni, Stefanos Eleftheriadis, James Hensman; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:689-697
Variational inference for the multi-armed contextual bandit
Iñigo Urteaga, Chris Wiggins; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:698-706
[abs][Download PDF]
Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods
Robert Gower, Nicolas Le Roux, Francis Bach; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:707-715
Subsampling for Ridge Regression via Regularized Volume Sampling
Michal Derezinski, Manfred Warmuth; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:716-725
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition
Pavel Izmailov, Alexander Novikov, Dmitry Kropotov; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:726-735
[abs][Download PDF]
Batch-Expansion Training: An Efficient Optimization Framework
Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:736-744
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Zi Wang, Clement Gehring, Pushmeet Kohli, Stefanie Jegelka; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:745-754
Temporally-Reweighted Chinese Restaurant Process Mixtures for Clustering, Imputing, and Forecasting Multivariate Time Series
Feras Saad, Vikash Mansinghka; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:755-764
Stochastic Three-Composite Convex Minimization with a Linear Operator
Renbo Zhao, Volkan Cevher; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:765-774
Direct Learning to Rank And Rerank
Cynthia Rudin, Yining Wang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:775-783
One-shot Coresets: The Case of k-Clustering
Olivier Bachem, Mario Lucic, Silvio Lattanzi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:784-792
Random Warping Series: A Random Features Method for Time-Series Embedding
Lingfei Wu, Ian En-Hsu Yen, Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:793-802
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh, Parijat Dube, Priya Nagpurkar; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:803-812
Variational Inference based on Robust Divergences
Futoshi Futami, Issei Sato, Masashi Sugiyama; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:813-822
Variational Rejection Sampling
Aditya Grover, Ramki Gummadi, Miguel Lazaro-Gredilla, Dale Schuurmans, Stefano Ermon; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:823-832
Best arm identification in multi-armed bandits with delayed feedback
Aditya Grover, Todor Markov, Peter Attia, Norman Jin, Nicolas Perkins, Bryan Cheong, Michael Chen, Zi Yang, Stephen Harris, William Chueh, Stefano Ermon; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:833-842
A fully adaptive algorithm for pure exploration in linear bandits
Liyuan Xu, Junya Honda, Masashi Sugiyama; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:843-851
Contextual Bandits with Stochastic Experts
Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:852-861
Human Interaction with Recommendation Systems
Sven Schmit, Carlos Riquelme; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:862-870
Community Detection in Hypergraphs: Optimal Statistical Limit and Efficient Algorithms
I Chien, Chung-Yi Lin, I-Hsiang Wang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:871-879
Smooth and Sparse Optimal Transport
Mathieu Blondel, Vivien Seguy, Antoine Rolet; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:880-889
Robust Maximization of Non-Submodular Objectives
Ilija Bogunovic, Junyao Zhao, Volkan Cevher; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:890-899
Cause-Effect Inference by Comparing Regression Errors
Patrick Bloebaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schoelkopf; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:900-909
[abs][Download PDF]
Tree-based Bayesian Mixture Model for Competing Risks
Alexis Bellot, Mihaela Schaar; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:910-918
[abs][Download PDF]
Actor-Critic Fictitious Play in Simultaneous Move Multistage Games
Julien Perolat, Bilal Piot, Olivier Pietquin; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:919-928
Random Subspace with Trees for Feature Selection Under Memory Constraints
Antonio Sutera, Célia Châtel, Gilles Louppe, Louis Wehenkel, Pierre Geurts; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:929-937
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information
Jakob Runge; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:938-947
Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures
Tomi Silander, Janne Leppä-aho, Elias Jääsaari, Teemu Roos; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:948-957
Convex Optimization over Intersection of Simple Sets: improved Convergence Rate Guarantees via an Exact Penalty Approach
Achintya Kundu, Francis Bach, Chiranjib Bhattacharya; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:958-967
Variational Sequential Monte Carlo
Christian Naesseth, Scott Linderman, Rajesh Ranganath, David Blei; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:968-977
Statistically Efficient Estimation for Non-Smooth Probability Densities
Masaaki Imaizumi, Takanori Maehara, Yuichi Yoshida; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:978-987
[abs][Download PDF]
SDCA-Powered Inexact Dual Augmented Lagrangian Method for Fast CRF Learning
Xu Hu, Guillaume Obozinski; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:988-997
Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression
Mathurin Massias, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:998-1007
Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models
Atsushi Nitanda, Taiji Suzuki; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1008-1016
Statistical Sparse Online Regression: A Diffusion Approximation Perspective
Jianqing Fan, Wenyan Gong, Chris Junchi Li, Qiang Sun; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1017-1026
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization
Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1027-1036
Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs
Lawrence Murray, Daniel Lundén, Jan Kudlicka, David Broman, Thomas Schön; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1037-1046
[abs][Download PDF]
Learning to Round for Discrete Labeling Problems
Pritish Mohapatra, Jawahar C.V., M Pawan Kumar; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1047-1056
[abs][Download PDF]
Approximate Ranking from Pairwise Comparisons
Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin Wainwright; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1057-1066
Semi-Supervised Prediction-Constrained Topic Models
Michael Hughes, Gabriel Hope, Leah Weiner, Thomas McCoy, Roy Perlis, Erik Sudderth, Finale Doshi-Velez; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1067-1076
A Stochastic Differential Equation Framework for Guiding Online User Activities in Closed Loop
Yichen Wang, Evangelos Theodorou, Apurv Verma, Le Song; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1077-1086
Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms
Pan Xu, Tianhao Wang, Quanquan Gu; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1087-1096
[abs][Download PDF]
A Unified Framework for Nonconvex Low-Rank plus Sparse Matrix Recovery
Xiao Zhang, Lingxiao Wang, Quanquan Gu; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1097-1107
Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling
Hongyi Ding, Mohammad Khan, Issei Sato, Masashi Sugiyama; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1108-1116
Factor Analysis on a Graph
Masayuki Karasuyama, Hiroshi Mamitsuka; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1117-1126
Crowdclustering with Partition Labels
Junxiang Chen, Yale Chang, Peter Castaldi, Michael Cho, Brian Hobbs, Jennifer Dy; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1127-1136
Learning Structural Weight Uncertainty for Sequential Decision-Making
Ruiyi Zhang, Chunyuan Li, Changyou Chen, Lawrence Carin; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1137-1146
Towards Memory-Friendly Deterministic Incremental Gradient Method
Jiahao Xie, Hui Qian, Zebang Shen, Chao Zhang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1147-1156
Optimality of Approximate Inference Algorithms on Stable Instances
Hunter Lang, David Sontag, Aravindan Vijayaraghavan; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1157-1166
Bayesian Approaches to Distribution Regression
Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic, Seth Flaxman; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1167-1176
Submodularity on Hypergraphs: From Sets to Sequences
Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1177-1184
[abs][Download PDF]
Provable Estimation of the Number of Blocks in Block Models
Bowei Yan, Purnamrita Sarkar, Xiuyuan Cheng; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1185-1194
[abs][Download PDF]
Differentially Private Regression with Gaussian Processes
Michael T. Smith, Mauricio A. Álvarez, Max Zwiessele, Neil D. Lawrence; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1195-1203
Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems
Sai Praneeth Reddy Karimireddy, Sebastian Stich, Martin Jaggi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1204-1213
VAE with a VampPrior
Jakub Tomczak, Max Welling; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1214-1223
Structured Factored Inference for Probabilistic Programming
Avi Pfeffer, Brian Ruttenberg, William Kretschmer, Alison OConnor; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1224-1232
A Generic Approach for Escaping Saddle points
Sashank Reddi, Manzil Zaheer, Suvrit Sra, Barnabas Poczos, Francis Bach, Ruslan Salakhutdinov, Alex Smola; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1233-1242
Policy Evaluation and Optimization with Continuous Treatments
Nathan Kallus, Angela Zhou; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1243-1251
Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations
Alan Lazarus, Dirk Husmeier, Theodore Papamarkou; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1252-1260
Why Adaptively Collected Data Have Negative Bias and How to Correct for It
Xinkun Nie, Xiaoying Tian, Jonathan Taylor, James Zou; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1261-1269
Sparse Linear Isotonic Models
Sheng Chen, Arindam Banerjee; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1270-1279
Robustness of classifiers to uniform $\ell_p$ and Gaussian noise
Jean-Yves Franceschi, Alhussein Fawzi, Omar Fawzi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1280-1288
Nested CRP with Hawkes-Gaussian Processes
Xi Tan, Vinayak Rao, Jennifer Neville; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1289-1298
[abs][Download PDF]
Sketching for Kronecker Product Regression and P-splines
Huaian Diao, Zhao Song, Wen Sun, David Woodruff; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1299-1308
Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models
Ardavan Saeedi, Matthew Hoffman, Stephen DiVerdi, Asma Ghandeharioun, Matthew Johnson, Ryan Adams; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1309-1317
Cheap Checking for Cloud Computing: Statistical Analysis via Annotated Data Streams
Chris Hickey, Graham Cormode; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1318-1326
Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning
Shashank Singh, Barnabas Poczos, Jian Ma; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1327-1336
Kernel Conditional Exponential Family
Michael Arbel, Arthur Gretton; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1337-1346
Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go?
Chandrashekar Lakshminarayanan, Csaba Szepesvari; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1347-1355
Stochastic Zeroth-order Optimization in High Dimensions
Yining Wang, Simon Du, Sivaraman Balakrishnan, Aarti Singh; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1356-1365
Teacher Improves Learning by Selecting a Training Subset
Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1366-1375
Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation
Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluc, Dmitriy Morozov, Leonid Oliker, Katherine Yelick, Sang-Yun Oh; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1376-1386
Robust Vertex Enumeration for Convex Hulls in High Dimensions
Pranjal Awasthi, Bahman Kalantari, Yikai Zhang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1387-1396
Fast generalization error bound of deep learning from a kernel perspective
Taiji Suzuki; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1397-1406
Product Kernel Interpolation for Scalable Gaussian Processes
Jacob Gardner, Geoff Pleiss, Ruihan Wu, Kilian Weinberger, Andrew Wilson; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1407-1416
Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation
Mohammadreza Soltani, Chinmay Hegde; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1417-1426
Scalable Generalized Dynamic Topic Models
Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1427-1435
Bayesian Structure Learning for Dynamic Brain Connectivity
Michael Andersen, Ole Winther, Lars Kai Hansen, Russell Poldrack, Oluwasanmi Koyejo; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1436-1446
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method
Mark Eisen, Aryan Mokhtari, Alejandro Ribeiro; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1447-1455
Frank-Wolfe Splitting via Augmented Lagrangian Method
Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1456-1465
Learning linear structural equation models in polynomial time and sample complexity
Asish Ghoshal, Jean Honorio; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1466-1475
Convergence diagnostics for stochastic gradient descent with constant learning rate
Jerry Chee, Panos Toulis; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1476-1485
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity
Asish Ghoshal, Jean Honorio; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1486-1494
Nonparametric Sharpe Ratio Function Estimation in Heteroscedastic Regression Models via Convex Optimization
Seung-Jean Kim, Johan Lim, Joong-Ho Won; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1495-1504
Stochastic algorithms for entropy-regularized optimal transport problems
Brahim Khalil Abid, Robert Gower; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1505-1512
[abs][Download PDF]
Plug-in Estimators for Conditional Expectations and Probabilities
Steffen Grunewalder; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1513-1521
Factorized Recurrent Neural Architectures for Longer Range Dependence
Francois Belletti, Alex Beutel, Sagar Jain, Ed Chi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1522-1530
[abs][Download PDF]
On the Statistical Efficiency of Compositional Nonparametric Prediction
Yixi Xu, Jean Honorio, Xiao Wang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1531-1539
Metrics for Deep Generative Models
Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick Smagt; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1540-1550
Combinatorial Penalties: Which structures are preserved by convex relaxations?
Marwa El Halabi, Francis Bach, Volkan Cevher; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1551-1560
Generalized Binary Search For Split-Neighborly Problems
Stephen Mussmann, Percy Liang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1561-1569
Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth
Jussi Viinikka, Ralf Eggeling, Mikko Koivisto; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1570-1578
On Statistical Optimality of Variational Bayes
Debdeep Pati, Anirban Bhattacharya, Yun Yang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1579-1588
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems
Jason Ge, Zhaoran Wang, Mengdi Wang, Han Liu; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1589-1598
Online Regression with Partial Information: Generalization and Linear Projection
Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-Ichi Kawarabayashi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1599-1607
Learning Generative Models with Sinkhorn Divergences
Aude Genevay, Gabriel Peyre, Marco Cuturi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1608-1617
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference
Scott Linderman, Gonzalo Mena, Hal Cooper, Liam Paninski, John Cunningham; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1618-1627
Achieving the time of 1-NN, but the accuracy of k-NN
Lirong Xue, Samory Kpotufe; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1628-1636
Efficient Weight Learning in High-Dimensional Untied MLNs
Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1637-1645
[abs][Download PDF]
Learning with Complex Loss Functions and Constraints
Harikrishna Narasimhan; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1646-1654
Solving lp-norm regularization with tensor kernels
Saverio Salzo, Lorenzo Rosasco, Johan Suykens; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1655-1663
Weighted Tensor Decomposition for Learning Latent Variables with Partial Data
Omer Gottesman, Weiwei Pan, Finale Doshi-Velez; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1664-1672
Multi-objective Contextual Bandit Problem with Similarity Information
Eralp Turgay, Doruk Oner, Cem Tekin; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1673-1681
Turing: A Language for Flexible Probabilistic Inference
Hong Ge, Kai Xu, Zoubin Ghahramani; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1682-1690
[abs][Download PDF]
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure
Beilun Wang, arshdeep Sekhon, Yanjun Qi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1691-1700
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
Sanket Kamthe, Marc Deisenroth; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1701-1710
Approximate Bayesian Computation with Kullback-Leibler Divergence as Data Discrepancy
Bai Jiang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1711-1721
Practical Bayesian optimization in the presence of outliers
Ruben Martinez-Cantin, Kevin Tee, Michael McCourt; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1722-1731
[abs][Download PDF]
Competing with Automata-based Expert Sequences
Mehryar Mohri, Scott Yang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1732-1740
Reducing Crowdsourcing to Graphon Estimation, Statistically
Devavrat Shah, Christina Lee; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1741-1750
Robust Locally-Linear Controllable Embedding
Ershad Banijamali, Rui Shu, mohammad Ghavamzadeh, Hung Bui, Ali Ghodsi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1751-1759
Combinatorial Semi-Bandits with Knapsacks
Karthik Abinav Sankararaman, Aleksandrs Slivkins; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1760-1770
Structured Optimal Transport
David Alvarez-Melis, Tommi Jaakkola, Stefanie Jegelka; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1771-1780
Graphical Models for Non-Negative Data Using Generalized Score Matching
Shiqing Yu, Mathias Drton, Ali Shojaie; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1781-1790
Asynchronous Doubly Stochastic Group Regularized Learning
Bin Gu, Zhouyuan Huo, Heng Huang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1791-1800
Convergence of Value Aggregation for Imitation Learning
Ching-An Cheng, Byron Boots; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1801-1809
Inference in Sparse Graphs with Pairwise Measurements and Side Information
Dylan Foster, Karthik Sridharan, Daniel Reichman; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1810-1818
Parallel and Distributed MCMC via Shepherding Distributions
Arkabandhu Chowdhury, Christopher Jermaine; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1819-1827
The Power Mean Laplacian for Multilayer Graph Clustering
Pedro Mercado, Antoine Gautier, Francesco Tudisco, Matthias Hein; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1828-1838
Adaptive Sampling for Coarse Ranking
Sumeet Katariya, Lalit Jain, Nandana Sengupta, James Evans, Robert Nowak; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1839-1848
Comparison Based Learning from Weak Oracles
Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1849-1858
The Binary Space Partitioning-Tree Process
Xuhui Fan, Bin Li, Scott Sisson; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1859-1867
On denoising modulo 1 samples of a function
Mihai Cucuringu, Hemant Tyagi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1868-1876
Scalable Hash-Based Estimation of Divergence Measures
Morteza Noshad, Alfred Hero; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1877-1885
[abs][Download PDF]
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap
Aryan Mokhtari, Hamed Hassani, Amin Karbasi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1886-1895
Online Continuous Submodular Maximization
Lin Chen, Hamed Hassani, Amin Karbasi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1896-1905
Efficient Bayesian Methods for Counting Processes in Partially Observable Environments
Ferdian Jovan, Jeremy Wyatt, Nick Hawes; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1906-1913
Matrix-normal models for fMRI analysis
Michael Shvartsman, Narayanan Sundaram, Mikio Aoi, Adam Charles, Theodore Willke, Jonathan Cohen; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1914-1923
The emergence of spectral universality in deep networks
Jeffrey Pennington, Samuel Schoenholz, Surya Ganguli; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1924-1932
Spectral Algorithms for Computing Fair Support Vector Machines
Mahbod Olfat, Anil Aswani; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1933-1942
[abs][Download PDF]
Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences
He Zhao, Piyush Rai, Lan Du, Wray Buntine; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1943-1951
[abs][Download PDF]
Nonparametric Bayesian sparse graph linear dynamical systems
Rahi Kalantari, Joydeep Ghosh, Mingyuan Zhou; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1952-1960
Proximity Variational Inference
Jaan Altosaar, Rajesh Ranganath, David Blei; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1961-1969
[abs][Download PDF]
Near-Optimal Machine Teaching via Explanatory Teaching Sets
Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1970-1978
Learning Hidden Quantum Markov Models
Siddarth Srinivasan, Geoff Gordon, Byron Boots; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1979-1987
Labeled Graph Clustering via Projected Gradient Descent
Shiau Hong Lim, Gregory Calvez; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1988-1997
[abs][Download PDF]
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning
Dong Yin, Ashwin Pananjady, Max Lam, Dimitris Papailiopoulos, Kannan Ramchandran, Peter Bartlett; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:1998-2007
HONES: A Fast and Tuning-free Homotopy Method For Online Newton Step
Yuting Ye, Lihua Lei, Cheng Ju; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:2008-2017
Probability–Revealing Samples
Krzysztof Onak, Xiaorui Sun; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:2018-2026
[abs][Download PDF]
Derivative Free Optimization Via Repeated Classification
Tatsunori Hashimoto, Steve Yadlowsky, John Duchi; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:2027-2036
[abs][Download PDF]
Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments
Yanning Shen, Tianyi Chen, Georgios Giannakis; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:2037-2046
A Unified Dynamic Approach to Sparse Model Selection
Chendi Huang, Yuan Yao; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:2047-2055
[abs][Download PDF]
Bootstrapping EM via Power EM and Convergence in the Naive Bayes Model
Costis Daskalakis, Christos Tzamos, Manolis Zampetakis; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:2056-2064
Dimensionality Reduced $\ell^{0}$-Sparse Subspace Clustering
Yingzhen Yang; Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:2065-2074
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。