Papers
Distributionally Robust Submodular Maximization
Matthew Staib, Bryan Wilder, Stefanie Jegelka
Testing Conditional Independence on Discrete Data using Stochastic Complexity
Alexander Marx, Jilles Vreeken
Local Saddle Point Optimization: A Curvature Exploitation Approach
Leonard Adolphs, Hadi Daneshmand, Aurelien Lucchi et al.
Efficient Bayesian Experimental Design for Implicit Models
Steven Kleinegesse, Michael U. Gutmann
An Optimal Algorithm for Stochastic and Adversarial Bandits
Julian Zimmert, Yevgeny Seldin
Sparse Multivariate Bernoulli Processes in High Dimensions
Parthe Pandit, Mojtaba Sahraee-Ardakan, Arash Amini et al.
Lifelong Optimization with Low Regret
Yi-Shan Wu, Po-An Wang, Chi-Jen Lu
A Thompson Sampling Algorithm for Cascading Bandits
Wang Chi Cheung, Vincent Tan, Zixin Zhong
An Optimal Algorithm for Stochastic Three-Composite Optimization
Renbo Zhao, William B. Haskell, Vincent Y. F. Tan
Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit
Yang Cao, Zheng Wen, Branislav Kveton et al.
Foundations of Sequence-to-Sequence Modeling for Time Series
Zelda Mariet, Vitaly Kuznetsov
Robust Matrix Completion from Quantized Observations
Jie Shen, Pranjal Awasthi, Ping Li
Learning Mixtures of Smooth Product Distributions: Identifiability and Algorithm
Nikos Kargas, Nicholas D. Sidiropoulos
Analysis of Network Lasso for Semi-Supervised Regression
Alexander Jung, Natalia Vesselinova
Performance Metric Elicitation from Pairwise Classifier Comparisons
Gaurush Hiranandani, Shant Boodaghians, Ruta Mehta et al.
Blind Demixing via Wirtinger Flow with Random Initialization
Jialin Dong, Yuanming Shi
Vine copula structure learning via Monte Carlo tree search
Bo Chang, Shenyi Pan, Harry Joe
Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning
Bo Liu, Xiao-Tong Yuan, Lezi Wang et al.
Pathwise Derivatives for Multivariate Distributions
Martin Jankowiak, Theofanis Karaletsos
Modularity-based Sparse Soft Graph Clustering
Alexandre Hollocou, Thomas Bonald, Marc Lelarge
Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems
Bhaskar Mukhoty, Govind Gopakumar, Prateek Jain et al.
Accelerated Coordinate Descent with Arbitrary Sampling and Best Rates for Minibatches
Filip Hanzely, Peter Richtarik
Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems
Dan Garber, Atara Kaplan
Near Optimal Algorithms for Hard Submodular Programs with Discounted Cooperative Costs
Rishabh Iyer, Jeffrey Bilmes