Papers
Fast Lifted MAP Inference via Partitioning
Somdeb Sarkhel, Parag Singla, Vibhav G Gogate
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach
Yinlam Chow, Aviv Tamar, Shie Mannor et al.
Testing Closeness With Unequal Sized Samples
Bhaswar Bhattacharya, Gregory Valiant
Sparse and Low-Rank Tensor Decomposition
Parikshit Shah, Nikhil Rao, Gongguo Tang
Fighting Bandits with a New Kind of Smoothness
Jacob D. Abernethy, Chansoo Lee, Ambuj Tewari
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions
Amar Shah, Zoubin Ghahramani
The Population Posterior and Bayesian Modeling on Streams
James McInerney, Rajesh Ranganath, David Blei
Revenue Optimization against Strategic Buyers
Mehryar Mohri, Andres Munoz
On the consistency theory of high dimensional variable screening
Xiangyu Wang, Chenlei Leng, David B Dunson
Spectral Representations for Convolutional Neural Networks
Oren Rippel, Jasper Snoek, Ryan P. Adams
Calibrated Structured Prediction
Volodymyr Kuleshov, Percy Liang
Nearly Optimal Private LASSO
Kunal Talwar, Abhradeep Guha Thakurta, Li Zhang
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
Mehrdad Farajtabar, Yichen Wang, Manuel Gomez Rodriguez et al.
Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders Diagnosis
Ehsan Adeli-Mosabbeb, Kim-Han Thung, Le An et al.
Winner-Take-All Autoencoders
Alireza Makhzani, Brendan J. Frey
Compressive spectral embedding: sidestepping the SVD
Dinesh Ramasamy, Upamanyu Madhow
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff
Ofer Dekel, Ronen Eldan, Tomer Koren
Particle Gibbs for Infinite Hidden Markov Models
Nilesh Tripuraneni, Shixiang (Shane) Gu, Hong Ge et al.
A Theory of Decision Making Under Dynamic Context
Michael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen
Learning to Segment Object Candidates
Pedro O O. Pinheiro, Ronan Collobert, Piotr Dollar
Minimax Time Series Prediction
Wouter M. Koolen, Alan Malek, Peter L Bartlett et al.
Robust Spectral Inference for Joint Stochastic Matrix Factorization
Moontae Lee, David Bindel, David Mimno
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
Jianshu Chen, Ji He, Yelong Shen et al.
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization
Fredrik D Johansson, Ankani Chattoraj, Chiranjib Bhattacharyya et al.