Papers
Distributed Exploration in Multi-Armed Bandits
Eshcar Hillel, Zohar S Karnin, Tomer Koren et al.
Reward Mapping for Transfer in Long-Lived Agents
Xiaoxiao Guo, Satinder Singh, Richard L. Lewis
Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation
John Duchi, Martin J. Wainwright, Michael I Jordan
Generalized Denoising Auto-Encoders as Generative Models
Yoshua Bengio, Li Yao, Guillaume Alain et al.
Parametric Task Learning
Ichiro Takeuchi, Tatsuya Hongo, Masashi Sugiyama et al.
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture
Trevor Campbell, Miao Liu, Brian Kulis et al.
Estimating the Unseen: Improved Estimators for Entropy and other Properties
Paul Valiant, Gregory Valiant
RNADE: The real-valued neural autoregressive density-estimator
Benigno Uria, Iain Murray, Hugo Larochelle
Online Variational Approximations to non-Exponential Family Change Point Models: With Application to Radar Tracking
Ryan D Turner, Steven Bottone, Clay J Stanek
Large Scale Distributed Sparse Precision Estimation
Huahua Wang, Arindam Banerjee, Cho-Jui Hsieh et al.
One-shot learning by inverting a compositional causal process
Brenden M Lake, Ruslan Salakhutdinov, Josh Tenenbaum
Streaming Variational Bayes
Tamara Broderick, Nicholas Boyd, Andre Wibisono et al.
Approximate Inference in Continuous Determinantal Processes
Raja Hafiz Affandi, Emily B. Fox, Ben Taskar
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions
Yasin Abbasi Yadkori, Peter L Bartlett, Varun Kanade et al.
Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis
James R Voss, Luis Rademacher, Mikhail Belkin
Learning the Local Statistics of Optical Flow
Dan Rosenbaum, Daniel Zoran, Yair Weiss
Robust Low Rank Kernel Embeddings of Multivariate Distributions
Le Song, Bo Dai
Causal Inference on Time Series using Restricted Structural Equation Models
Jonas Peters, Dominik Janzing, Bernhard Schölkopf
Robust learning of low-dimensional dynamics from large neural ensembles
David Pfau, Eftychios A Pnevmatikakis, Liam Paninski
Efficient Optimization for Sparse Gaussian Process Regression
Yanshuai Cao, Marcus A Brubaker, David J Fleet et al.
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation
Martin Azizyan, Aarti Singh, Larry Wasserman
Factorized Asymptotic Bayesian Inference for Latent Feature Models
Kohei Hayashi, Ryohei Fujimaki