Papers
AdaDelay: Delay Adaptive Distributed Stochastic Optimization
Suvrit Sra, Adams Wei Yu, Mu Li et al.
Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces
Amirali Abdullah, Ravi Kumar, Andrew McGregor et al.
Pareto Front Identification from Stochastic Bandit Feedback
Peter Auer, Chao-Kai Chiang, Ronald Ortner et al.
Ordered Weighted L1 Regularized Regression with Strongly Correlated Covariates: Theoretical Aspects
Mario Figueiredo, Robert Nowak
How to Learn a Graph from Smooth Signals
Vassilis Kalofolias
Pseudo-Marginal Slice Sampling
Iain Murray, Matthew Graham
Semi-Supervised Learning with Adaptive Spectral Transform
Hanxiao Liu, Yiming Yang
On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games
Julien Pérolat, Bilal Piot, Bruno Scherrer et al.
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models
Chun-Liang Li, Kirthevasan Kandasamy, Barnabas Poczos et al.
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections
Christina Heinze, Brian McWilliams, Nicolai Meinshausen
Model-based Co-clustering for High Dimensional Sparse Data
Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif
Scalable geometric density estimation
Ye Wang, Antonio Canale, David Dunson
Accelerating Online Convex Optimization via Adaptive Prediction
Mehryar Mohri, Scott Yang
Low-Rank Approximation of Weighted Tree Automata
Guillaume Rabusseau, Borja Balle, Shay Cohen
Variational Gaussian Copula Inference
Shaobo Han, Xuejun Liao, David Dunson et al.
(Bandit) Convex Optimization with Biased Noisy Gradient Oracles
Xiaowei Hu, Prashanth L.A., András György et al.
Stochastic Neural Networks with Monotonic Activation Functions
Siamak Ravanbakhsh, Barnabas Poczos, Jeff Schneider et al.
Stochastic Variational Inference for the HDP-HMM
Aonan Zhang, San Gultekin, John Paisley
GLASSES: Relieving The Myopia Of Bayesian Optimisation
Javier Gonzalez, Michael Osborne, Neil Lawrence
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm
Sangkyun Lee, Damian Brzyski, Malgorzata Bogdan
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation
Sebastian Tschiatschek, Josip Djolonga, Andreas Krause
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models
Rishit Sheth, Roni Khardon
Distributed Multi-Task Learning
Jialei Wang, Mladen Kolar, Nathan Srerbo
A Deep Generative Deconvolutional Image Model
Yunchen Pu, Win Yuan, Andrew Stevens et al.
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
Markus Heinonen, Henrik Mannerström, Juho Rousu et al.