Stochastic Methods

On Markov Chain Gradient Descent NeurIPS 2018 On Nesting Monte Carlo Estimators ICML 2018 On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization IJCAI 2018 On the Efficiency of Data Collection for Crowdsourced Classification IJCAI 2018 On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo ICML 2018 Open Loop Execution of Tree-Search Algorithms IJCAI 2018 Optimistic optimization of a Brownian NeurIPS 2018 Parallelised Bayesian Optimisation via Thompson Sampling AISTATS 2018 Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification JMLR 2018 Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks NeurIPS 2018 Patchwork Kriging for Large-scale Gaussian Process Regression JMLR 2018 Planning and Learning with Stochastic Action Sets IJCAI 2018 Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences NeurIPS 2018 Probabilistic Joint Face-Skull Modelling for Facial Reconstruction CVPR 2018 Quantum Divide-and-Conquer Anchoring for Separable Non-negative Matrix Factorization IJCAI 2018 Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes NeurIPS 2018 Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis AISTATS 2018 Riemannian Stochastic Recursive Gradient Algorithm ICML 2018 SADAGRAD: Strongly Adaptive Stochastic Gradient Methods ICML 2018 Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation NeurIPS 2018 Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem COLT 2018 Sampling-Based Approximation Algorithms for Reachability Analysis with Provable Guarantees RSS 2018 Scaling the Poisson GLM to massive neural datasets through polynomial approximations NeurIPS 2018 Scaling up Data Augmentation MCMC via Calibration JMLR 2018 SGD and Hogwild! Convergence Without the Bounded Gradients Assumption ICML 2018