Papers
Efficient Bandit Combinatorial Optimization Algorithm with Zero-suppressed Binary Decision Diagrams
Shinsaku Sakaue, Masakazu Ishihata, Shin-ichi Minato
Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes
Hyunjik Kim, Yee Whye Teh
A Provable Algorithm for Learning Interpretable Scoring Systems
Nataliya Sokolovska, Yann Chevaleyre, Jean-Daniel Zucker
Group Invariance Principles for Causal Generative Models
Michel Besserve, Naji Shajarisales, Bernhard Schölkopf et al.
Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods
Stephan Clémençon, François Portier
Exploiting Strategy-Space Diversity for Batch Bayesian Optimization
Sunil Gupta, Alistair Shilton, Santu Rana et al.
Sum-Product-Quotient Networks
Or Sharir, Amnon Shashua
Nearly second-order optimality of online joint detection and estimation via one-sample update schemes
Yang Cao, Liyan Xie, Yao Xie et al.
Regional Multi-Armed Bandits
Zhiyang Wang, Ruida Zhou, Cong Shen
Medoids in Almost-Linear Time via Multi-Armed Bandits
Vivek Bagaria, Govinda Kamath, Vasilis Ntranos et al.
A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization
Emanuel Laude, Tao Wu, Daniel Cremers
Tensor Regression Meets Gaussian Processes
Rose Yu, Guangyu Li, Yan Liu
Personalized and Private Peer-to-Peer Machine Learning
Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki et al.
Boosting Variational Inference: an Optimization Perspective
Francesco Locatello, Rajiv Khanna, Joydeep Ghosh et al.
Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables
Masaaki Takada, Taiji Suzuki, Hironori Fujisawa
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer
Tianbao Yang, Zhe Li, Lijun Zhang
Dropout as a Low-Rank Regularizer for Matrix Factorization
Jacopo Cavazza, Pietro Morerio, Benjamin Haeffele et al.
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
William Herlands, Edward McFowland, Andrew Wilson et al.
Multi-view Metric Learning in Vector-valued Kernel Spaces
Riikka Huusari, Hachem Kadri, Cécile Capponi
FLAG n’ FLARE: Fast Linearly-Coupled Adaptive Gradient Methods
Xiang Cheng, Fred Roosta, Stefan Palombo et al.
Matrix completability analysis via graph k-connectivity
Dehua Cheng, Natali Ruchansky, Yan Liu
Stochastic Multi-armed Bandits in Constant Space
David Liau, Zhao Song, Eric Price et al.
Optimal Cooperative Inference
Scott Cheng-Hsin Yang, Yue Yu, arash Givchi et al.
Learning Priors for Invariance
Eric Nalisnick, Padhraic Smyth
Topic Compositional Neural Language Model
Wenlin Wang, Zhe Gan, Wenqi Wang et al.