Stochastic Processes

Cascading Bandits: Learning to Rank in the Cascade Model ICML 2015 COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution NeurIPS 2015 Convergence rates of sub-sampled Newton methods NeurIPS 2015 Cornering Stationary and Restless Mixing Bandits with Remix-UCB NeurIPS 2015 Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation AISTATS 2015 Efficient Training of LDA on a GPU by Mean-for-Mode Estimation ICML 2015 Exploiting Symmetries to Construct Efficient MCMC Algorithms With an Application to SLAM AISTATS 2015 Fast and Accurate Inference of Plackett–Luce Models NeurIPS 2015 Fast Bidirectional Probability Estimation in Markov Models NeurIPS 2015 Fast Mixing for Discrete Point Processes COLT 2015 Finite-Time Analysis of Projected Langevin Monte Carlo NeurIPS 2015 Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems ICML 2015 Gradient Estimation Using Stochastic Computation Graphs NeurIPS 2015 Guidance and Navigation for UAV Airborne Docking RSS 2015 Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs ICML 2015 Inverting RANSAC: Global Model Detection via Inlier Rate Estimation CVPR 2015 JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes ICML 2015 Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data ICML 2015 Learning Fast-Mixing Models for Structured Prediction ICML 2015 Learning from Data with Heterogeneous Noise using SGD AISTATS 2015 Links Between Multiplicity Automata, Observable Operator Models and Predictive State Representations -- a Unified Learning Framework JMLR 2015 Markov Chain Monte Carlo and Variational Inference: Bridging the Gap ICML 2015 Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets NeurIPS 2015 MCMC Learning COLT 2015 Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards JMLR 2015