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Stochastic Methods

2788 directly classified papers

Papers per year

Papers

Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions ICML 2023
A theory of representation learning gives a deep generalisation of kernel methods ICML 2023
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds ICML 2023
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions NIPS 2023
Towards Quantum Machine Learning for Constrained Combinatorial Optimization: a Quantum QAP Solver ICML 2023
Breaking a Classical Barrier for Classifying Arbitrary Test Examples in the Quantum Model AISTATS 2023
Regularized online DR-submodular optimization UAI 2023
Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond NIPS 2023
Optimal Sketching Bounds for Sparse Linear Regression AISTATS 2023
A Novel Demand Response Model and Method for Peak Reduction in Smart Grids -- PowerTAC IJCAI 2023
Concurrent Shuffle Differential Privacy Under Continual Observation ICML 2023
Optimal Preconditioning and Fisher Adaptive Langevin Sampling NIPS 2023
Tighter Analysis for ProxSkip ICML 2023
A Quantitative Game-theoretical Study on Externalities of Long-lasting Humanitarian Relief Operations in Conflict Areas IJCAI 2023
Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws AISTATS 2023
Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization NIPS 2023
Mixtures of All Trees AISTATS 2023
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent AISTATS 2023
Wasserstein Distributional Learning via Majorization-Minimization AISTATS 2023
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization ICML 2023
Score-based Quickest Change Detection for Unnormalized Models AISTATS 2023
Stochastic Optimization for Spectral Risk Measures AISTATS 2023
Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023
PAC-Bayesian Learning of Optimization Algorithms AISTATS 2023
A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging NIPS 2023