Stochastic Methods

Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity NeurIPS 2024 Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning NeurIPS 2024 SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization NeurIPS 2024 Small coresets via negative dependence: DPPs, linear statistics, and concentration NeurIPS 2024 Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates NeurIPS 2024 SPO: Sequential Monte Carlo Policy Optimisation NeurIPS 2024 Stepping Forward on the Last Mile NeurIPS 2024 Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality JMLR 2024 Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling AISTATS 2024 Stochastic Multi-Armed Bandits with Strongly Reward-Dependent Delays AISTATS 2024 Stochastic Optimal Control for Diffusion Bridges in Function Spaces NeurIPS 2024 Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data NeurIPS 2024 Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss NeurIPS 2024 Surrogate Active Subspaces for Jump-Discontinuous Functions AISTATS 2024 Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems ICLR 2024 Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces NeurIPS 2024 Taming Heavy-Tailed Losses in Adversarial Bandits and the Best-of-Both-Worlds Setting NeurIPS 2024 Text Is MASS: Modeling as Stochastic Embedding for Text-Video Retrieval CVPR 2024 The Price of Adaptivity in Stochastic Convex Optimization COLT 2024 The surprising efficiency of temporal difference learning for rare event prediction NeurIPS 2024 Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NeurIPS 2024 Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective NeurIPS 2024 Towards Exact Gradient-based Training on Analog In-memory Computing NeurIPS 2024 Towards Stability and Generalization Bounds in Decentralized Minibatch Stochastic Gradient Descent AAAI 2024 Understanding Progressive Training Through the Framework of Randomized Coordinate Descent AISTATS 2024