Papers
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
Xingguo Li, Tuo Zhao, Raman Arora et al.
A PAC RL Algorithm for Episodic POMDPs
Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill
Approximate Inference Using DC Programming For Collective Graphical Models
Thien Nguyen, Akshat Kumar, Hoong Chuin Lau et al.
A Robust-Equitable Copula Dependence Measure for Feature Selection
Yale Chang, Yi Li, Adam Ding et al.
Back to the Future: Radial Basis Function Networks Revisited
Qichao Que, Mikhail Belkin
(Bandit) Convex Optimization with Biased Noisy Gradient Oracles
Xiaowei Hu, Prashanth L.A., András György et al.
Batch Bayesian Optimization via Local Penalization
Javier Gonzalez, Zhenwen Dai, Philipp Hennig et al.
Bayesian Generalised Ensemble Markov Chain Monte Carlo
Jes Frellsen, Ole Winther, Zoubin Ghahramani et al.
Bayesian Markov Blanket Estimation
Dinu Kaufmann, Sonali Parbhoo, Aleksander Wieczorek et al.
Bayesian Nonparametric Kernel-Learning
Junier B. Oliva, Avinava Dubey, Andrew G. Wilson et al.
Bayes-Optimal Effort Allocation in Crowdsourcing: Bounds and Index Policies
Weici Hu, Peter Frazier
Bethe Learning of Graphical Models via MAP Decoding
Kui Tang, Nicholas Ruozzi, David Belanger et al.
Bipartite Correlation Clustering: Maximizing Agreements
Megasthenis Asteris, Anastasios Kyrillidis, Dimitris Papailiopoulos et al.
Black-Box Policy Search with Probabilistic Programs
Jan-Willem Vandemeent, Brooks Paige, David Tolpin et al.
Breaking Sticks and Ambiguities with Adaptive Skip-gram
Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin et al.
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization
Changyou Chen, David Carlson, Zhe Gan et al.
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching
Daniel Ritchie, Andreas Stuhlmüller, Noah Goodman
Chained Gaussian Processes
Alan D. Saul, James Hensman, Aki Vehtari et al.
Clamping Improves TRW and Mean Field Approximations
Adrian Weller, Justin Domke
Communication Efficient Distributed Agnostic Boosting
Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models
Andreas Svensson, Arno Solin, Simo Särkkä et al.
Consistently Estimating Markov Chains with Noisy Aggregate Data
Garrett Bernstein, Daniel Sheldon
Control Functionals for Quasi-Monte Carlo Integration
Chris Oates, Mark Girolami
Controlling Bias in Adaptive Data Analysis Using Information Theory
Daniel Russo, James Zou
Convex Block-sparse Linear Regression with Expanders – Provably
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad et al.