Stochastic Methods

A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery ICML 2017 Automatic Time-Frequency Analysis of Echolocation Signals Using the Matched Gaussian Multitaper Spectrogram Interspeech 2017 Bernoulli Rank-1 Bandits for Click Feedback IJCAI 2017 Beyond the Nystrom Approximation: Speeding up Spectral Clustering using Uniform Sampling and Weighted Kernel k-means IJCAI 2017 Black-box Importance Sampling AISTATS 2017 Boundary Crossing for General Exponential Families ALT 2017 Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization NeurIPS 2017 Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction NeurIPS 2017 Capacity Releasing Diffusion for Speed and Locality ICML 2017 Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling NeurIPS 2017 Coded Distributed Computing for Inverse Problems NeurIPS 2017 COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution JMLR 2017 Concentration of Multilinear Functions of the Ising Model with Applications to Network Data NeurIPS 2017 Conditional Accelerated Lazy Stochastic Gradient Descent ICML 2017 Counterfactual Learning from Bandit Feedback under Deterministic Logging : A Case Study in Statistical Machine Translation EMNLP 2017 CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC AISTATS 2017 Crowd Learning: Improving Online Decision Making Using Crowdsourced Data IJCAI 2017 Deformable Rapidly-Exploring Random Trees RSS 2017 Discovering and Exploiting Additive Structure for Bayesian Optimization AISTATS 2017 Distributed Batch Gaussian Process Optimization ICML 2017 Distributed Mean Estimation with Limited Communication ICML 2017 Diving into the shallows: a computational perspective on large-scale shallow learning NeurIPS 2017 DPSCREEN: Dynamic Personalized Screening NeurIPS 2017 Dueling Bandits with Weak Regret ICML 2017 Dynamic Importance Sampling for Anytime Bounds of the Partition Function NeurIPS 2017