Papers
Multivariate tests of association based on univariate tests
Ruth Heller, Yair Heller
Online and Differentially-Private Tensor Decomposition
Yining Wang, Anima Anandkumar
Deep Learning for Predicting Human Strategic Behavior
Jason S Hartford, James R Wright, Kevin Leyton-Brown
Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain
Ian En-Hsu Yen, Xiangru Huang, Kai Zhong et al.
SoundNet: Learning Sound Representations from Unlabeled Video
Yusuf Aytar, Carl Vondrick, Antonio Torralba
Composing graphical models with neural networks for structured representations and fast inference
Matthew J Johnson, David K. Duvenaud, Alex Wiltschko et al.
Robustness of classifiers: from adversarial to random noise
Alhussein Fawzi, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard
Automated scalable segmentation of neurons from multispectral images
Uygar Sümbül, Douglas Roossien, Dawen Cai et al.
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Xi Chen, Yan Duan, Rein Houthooft et al.
Selective inference for group-sparse linear models
Fan Yang, Rina Foygel Barber, Prateek Jain et al.
Discriminative Gaifman Models
Mathias Niepert
Clustering Signed Networks with the Geometric Mean of Laplacians
Pedro Mercado, Francesco Tudisco, Matthias Hein
Improved Dropout for Shallow and Deep Learning
Zhe Li, Boqing Gong, Tianbao Yang
Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages
Yin Cheng Ng, Pawel M Chilinski, Ricardo Silva
Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning
Jean-Bastien Grill, Michal Valko, Remi Munos
A Minimax Approach to Supervised Learning
Farzan Farnia, David Tse
Estimating the class prior and posterior from noisy positives and unlabeled data
Shantanu Jain, Martha White, Predrag Radivojac
Stochastic Structured Prediction under Bandit Feedback
Artem Sokolov, Julia Kreutzer, Stefan Riezler et al.
Global Analysis of Expectation Maximization for Mixtures of Two Gaussians
Ji Xu, Daniel J. Hsu, Arian Maleki
A posteriori error bounds for joint matrix decomposition problems
Nicolo Colombo, Nikos Vlassis
Stochastic Gradient Geodesic MCMC Methods
Chang Liu, Jun Zhu, Yang Song
Rényi Divergence Variational Inference
Yingzhen Li, Richard E Turner
Linear dynamical neural population models through nonlinear embeddings
Yuanjun Gao, Evan W Archer, Liam Paninski et al.
Boosting with Abstention
Corinna Cortes, Giulia DeSalvo, Mehryar Mohri