Papers
Gaussian process nonparametric tensor estimator and its minimax optimality
Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi et al.
Black-box Optimization with a Politician
Sebastien Bubeck, Yin Tat Lee
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification
Andre Martins, Ramon Astudillo
On collapsed representation of hierarchical Completely Random Measures
Gaurav Pandey, Ambedkar Dukkipati
Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design
William Hoiles, Mihaela Schaar
Anytime optimal algorithms in stochastic multi-armed bandits
Rémy Degenne, Vianney Perchet
Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling
Atsushi Shibagaki, Masayuki Karasuyama, Kohei Hatano et al.
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling
Christopher De Sa, Chris Re, Kunle Olukotun
Autoencoding beyond pixels using a learned similarity metric
Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle et al.
Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms
Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai et al.
A ranking approach to global optimization
Cedric Malherbe, Emile Contal, Nicolas Vayatis
Optimal Classification with Multivariate Losses
Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar et al.
One-Shot Generalization in Deep Generative Models
Danilo Rezende, Shakir, Ivo Danihelka et al.
Black-Box Alpha Divergence Minimization
Jose Hernandez-Lobato, Yingzhen Li, Mark Rowland et al.
Rich Component Analysis
Rong Ge, James Zou
Predictive Entropy Search for Multi-objective Bayesian Optimization
Daniel Hernandez-Lobato, Jose Hernandez-Lobato, Amar Shah et al.
DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression
Jovana Mitrovic, Dino Sejdinovic, Yee-Whye Teh
Deep Gaussian Processes for Regression using Approximate Expectation Propagation
Thang Bui, Daniel Hernandez-Lobato, Jose Hernandez-Lobato et al.
Starting Small - Learning with Adaptive Sample Sizes
Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann
Importance Sampling Tree for Large-scale Empirical Expectation
Olivier Canevet, Cijo Jose, Francois Fleuret
Auxiliary Deep Generative Models
Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby et al.
Extreme F-measure Maximization using Sparse Probability Estimates
Kalina Jasinska, Krzysztof Dembczynski, Robert Busa-Fekete et al.
Non-negative Matrix Factorization under Heavy Noise
Chiranjib Bhattacharya, Navin Goyal, Ravindran Kannan et al.
Estimating Accuracy from Unlabeled Data: A Bayesian Approach
Emmanouil Antonios Platanios, Avinava Dubey, Tom Mitchell
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control
Prashanth L.A., Cheng Jie, Michael Fu et al.