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Stochastic Methods

2788 directly classified papers

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Papers

Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization NIPS 2020
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev NIPS 2020
DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate AISTATS 2020
Online Learning Using Only Peer Prediction AISTATS 2020
Stochastic Online Learning with Probabilistic Graph Feedback AAAI 2020
Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients AAAI 2020
Optimization of Chance-Constrained Submodular Functions AAAI 2020
Communication, Distortion, and Randomness in Metric Voting AAAI 2020
Sampling Random Chordal Graphs by MCMC (Student Abstract) AAAI 2020
Effectively Unbiased FID and Inception Score and Where to Find Them CVPR 2020
A Class of Algorithms for General Instrumental Variable Models NIPS 2020
Predicting Training Time Without Training NIPS 2020
Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max Optimization NIPS 2020
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent NIPS 2020
Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NIPS 2020
Random Reshuffling is Not Always Better NIPS 2020
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits NIPS 2020
Black-Box Ripper: Copying black-box models using generative evolutionary algorithms NIPS 2020
Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations NIPS 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton NIPS 2020
A Randomized Algorithm to Reduce the Support of Discrete Measures NIPS 2020
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time NIPS 2020
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy AAAI 2020
Truncated Linear Regression in High Dimensions NIPS 2020
Stochastic Optimization with Laggard Data Pipelines NIPS 2020