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Stochastic Methods

2,788 papers

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Papers

Adaptation to Misspecified Kernel Regularity in Kernelised Bandits AISTATS 2023
Optimal Contextual Bandits with Knapsacks under Realizability via Regression Oracles AISTATS 2023
A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization AISTATS 2023
Complex-to-Real Sketches for Tensor Products with Applications to the Polynomial Kernel AISTATS 2023
A Faster Sampler for Discrete Determinantal Point Processes AISTATS 2023
Stochastic Mirror Descent for Large-Scale Sparse Recovery AISTATS 2023
High Probability Bounds for Stochastic Continuous Submodular Maximization AISTATS 2023
Average Adjusted Association: Efficient Estimation with High Dimensional Confounders AISTATS 2023
Discrete Langevin Samplers via Wasserstein Gradient Flow AISTATS 2023
SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals AISTATS 2023
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources AISTATS 2023
Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback AISTATS 2023
Incremental Aggregated Riemannian Gradient Method for Distributed PCA AISTATS 2023
No time to waste: practical statistical contact tracing with few low-bit messages AISTATS 2023
Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games AISTATS 2023
Adaptive Tuning for Metropolis Adjusted Langevin Trajectories AISTATS 2023
PAC-Bayesian Learning of Optimization Algorithms AISTATS 2023
Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints AISTATS 2023
Preferential Subsampling for Stochastic Gradient Langevin Dynamics AISTATS 2023
Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023
Large deviations rates for stochastic gradient descent with strongly convex functions AISTATS 2023
Stochastic Optimization for Spectral Risk Measures AISTATS 2023
Score-based Quickest Change Detection for Unnormalized Models AISTATS 2023
Wasserstein Distributional Learning via Majorization-Minimization AISTATS 2023
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent AISTATS 2023