Papers
A Framework for Testing Identifiability of Bayesian Models of Perception
Luigi Acerbi, Wei Ji Ma, Sethu Vijayakumar
Learning Deep Features for Scene Recognition using Places Database
Bolei Zhou, Agata Lapedriza, Jianxiong Xiao et al.
Mondrian Forests: Efficient Online Random Forests
Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh
On Model Parallelization and Scheduling Strategies for Distributed Machine Learning
Seunghak Lee, Jin Kyu Kim, Xun Zheng et al.
Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data
Karthika Mohan, Judea Pearl
Probabilistic low-rank matrix completion on finite alphabets
Jean Lafond, Olga Klopp, Eric Moulines et al.
Efficient Minimax Strategies for Square Loss Games
Wouter M. Koolen, Alan Malek, Peter L Bartlett
Low Rank Approximation Lower Bounds in Row-Update Streams
David Woodruff
Extreme bandits
Alexandra Carpentier, Michal Valko
Compressive Sensing of Signals from a GMM with Sparse Precision Matrices
Jianbo Yang, Xuejun Liao, Minhua Chen et al.
Dimensionality Reduction with Subspace Structure Preservation
Devansh Arpit, Ifeoma Nwogu, Venu Govindaraju
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks
Mario Marchand, Hongyu Su, Emilie Morvant et al.
Sequential Monte Carlo for Graphical Models
Christian Andersson Naesseth, Fredrik Lindsten, Thomas B Schön
Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs
David I Inouye, Pradeep K Ravikumar, Inderjit S Dhillon
Exact Post Model Selection Inference for Marginal Screening
Jason Lee, Jonathan E Taylor
Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization
Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo et al.
Covariance shrinkage for autocorrelated data
Daniel Bartz, Klaus-Robert Müller
RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning
Marek Petrik, Dharmashankar Subramanian
SerialRank: Spectral Ranking using Seriation
Fajwel Fogel, Alexandre d'Aspremont, Milan Vojnovic
Difference of Convex Functions Programming for Reinforcement Learning
Bilal Piot, Matthieu Geist, Olivier Pietquin
Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning
Brendan McMahan, Matthew Streeter
Near-optimal Reinforcement Learning in Factored MDPs
Ian Osband, Benjamin Van Roy
Extracting Latent Structure From Multiple Interacting Neural Populations
Joao Semedo, Amin Zandvakili, Adam Kohn et al.
Conditional Swap Regret and Conditional Correlated Equilibrium
Mehryar Mohri, Scott Yang
Optimal prior-dependent neural population codes under shared input noise
Agnieszka Grabska-Barwinska, Jonathan W Pillow