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Stochastic Methods

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Papers

Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency AISTATS 2021
Shadow Manifold Hamiltonian Monte Carlo AISTATS 2021
Learning Complexity of Simulated Annealing AISTATS 2021
Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery AISTATS 2021
Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features AISTATS 2021
vqSGD: Vector Quantized Stochastic Gradient Descent AISTATS 2021
Federated Learning with Compression: Unified Analysis and Sharp Guarantees AISTATS 2021
Shuffled Model of Differential Privacy in Federated Learning AISTATS 2021
Random Coordinate Underdamped Langevin Monte Carlo AISTATS 2021
Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression AISTATS 2021
Multi-Armed Bandits with Cost Subsidy AISTATS 2021
Experimental Design for Regret Minimization in Linear Bandits AISTATS 2021
A Hybrid Approximation to the Marginal Likelihood AISTATS 2021
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC AISTATS 2021
Rao-Blackwellised parallel MCMC AISTATS 2021
Calibrated Adaptive Probabilistic ODE Solvers AISTATS 2021
Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information AISTATS 2021
Sequential Random Sampling Revisited: Hidden Shuffle Method AISTATS 2021
Couplings for Multinomial Hamiltonian Monte Carlo AISTATS 2021
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models AISTATS 2021
Direct-Search for a Class of Stochastic Min-Max Problems AISTATS 2021
Combinatorial Gaussian Process Bandits with Probabilistically Triggered Arms AISTATS 2021
Regret Minimization in Heavy-Tailed Bandits COLT 2021
Non-Euclidean Differentially Private Stochastic Convex Optimization COLT 2021
Multiplayer Bandit Learning, from Competition to Cooperation COLT 2021