← Optimization & Theory
Machine Learning › Optimization & Theory ›

Stochastic Methods

1077 directly classified papers

Papers per year

Papers

Simulation and Calibration of a Fully Bayesian Marked Multidimensional Hawkes Process with Dissimilar Decays ACML 2016
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization NIPS 2016
Exploration of the (Non-)Asymptotic Bias and Variance of Stochastic Gradient Langevin Dynamics JMLR 2016
Scalable Adaptive Stochastic Optimization Using Random Projections NIPS 2016
Delay and Cooperation in Nonstochastic Bandits COLT 2016
Stochastic Variance Reduction for Nonconvex Optimization ICML 2016
Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models ACML 2015
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization ICML 2015
Stochastic Online Greedy Learning with Semi-bandit Feedbacks NIPS 2015
Stochastic Optimization with Importance Sampling for Regularized Loss Minimization ICML 2015
A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate ICML 2015
Stochastic Dual Coordinate Ascent with Adaptive Probabilities ICML 2015
Cheap Bandits ICML 2015
Generalized Tensor Total Variation Minimization for Visual Data Recovery CVPR 2015
Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) ICML 2015
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care NIPS 2015
Convergence rates of sub-sampled Newton methods NIPS 2015
Learning with Incremental Iterative Regularization NIPS 2015
Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling NIPS 2015
Inference in a Partially Observed Queuing Model with Applications in Ecology ICML 2015
Joint Inference of Groups, Events and Human Roles in Aerial Videos CVPR 2015
Nested Sequential Monte Carlo Methods ICML 2015
Stochastic Spectral Descent for Restricted Boltzmann Machines AISTATS 2015
The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling ICML 2015
Fast and Accurate Inference of Plackett–Luce Models NIPS 2015