Papers
Maximal Sparsity with Deep Networks?
Bo Xin, Yizhou Wang, Wen Gao et al.
Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models
Juho Lee, Lancelot F James, Seungjin Choi
Variational Bayes on Monte Carlo Steroids
Aditya Grover, Stefano Ermon
Threshold Bandits, With and Without Censored Feedback
Jacob D. Abernethy, Kareem Amin, Ruihao Zhu
Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction
Jacob Steinhardt, Gregory Valiant, Moses Charikar
Finding significant combinations of features in the presence of categorical covariates
Laetitia Papaxanthos, Felipe Llinares-López, Dean Bodenham et al.
Interpretable Distribution Features with Maximum Testing Power
Wittawat Jitkrittum, Zoltán Szabó, Kacper P Chwialkowski et al.
Bi-Objective Online Matching and Submodular Allocations
Hossein Esfandiari, Nitish Korula, Vahab Mirrokni
A Sparse Interactive Model for Matrix Completion with Side Information
Jin Lu, Guannan Liang, Jiangwen Sun et al.
An equivalence between high dimensional Bayes optimal inference and M-estimation
Madhu Advani, Surya Ganguli
Budgeted stream-based active learning via adaptive submodular maximization
Kaito Fujii, Hisashi Kashima
Convolutional Neural Fabrics
Shreyas Saxena, Jakob Verbeek
Automatic Neuron Detection in Calcium Imaging Data Using Convolutional Networks
Noah Apthorpe, Alexander Riordan, Robert Aguilar et al.
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks
Yarin Gal, Zoubin Ghahramani
Dialog-based Language Learning
Jason E Weston
Integrated perception with recurrent multi-task neural networks
Hakan Bilen, Andrea Vedaldi
A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics
William Hoiles, Mihaela van der Schaar
Exponential Family Embeddings
Maja Rudolph, Francisco Ruiz, Stephan Mandt et al.
Fast Distributed Submodular Cover: Public-Private Data Summarization
Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Michaël Defferrard, Xavier Bresson, Pierre Vandergheynst
Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods
Andrej Risteski, Yuanzhi Li
Generating Videos with Scene Dynamics
Carl Vondrick, Hamed Pirsiavash, Antonio Torralba
Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo
Alain Durmus, Umut Simsekli, Eric Moulines et al.
Achieving budget-optimality with adaptive schemes in crowdsourcing
Ashish Khetan, Sewoong Oh