Stochastic Methods

Information-constrained optimization: can adaptive processing of gradients help? NeurIPS 2021 Integrated Optimization of Bipartite Matching and Its Stochastic Behavior: New Formulation and Approximation Algorithm via Min-cost Flow Optimization AAAI 2021 Joint Online Multichannel Acoustic Echo Cancellation, Speech Dereverberation and Source Separation Interspeech 2021 KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support NeurIPS 2021 Kernel Stein Discrepancy Descent ICML 2021 Kernel Thinning COLT 2021 Langevin Monte Carlo: random coordinate descent and variance reduction JMLR 2021 Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds NeurIPS 2021 Learning by Watching CVPR 2021 Learning Complexity of Simulated Annealing AISTATS 2021 Learning Deep Latent Variable Models by Short-Run MCMC Inference With Optimal Transport Correction CVPR 2021 Learning in Markets: Greed Leads to Chaos but Following the Price is Right IJCAI 2021 Learning interaction kernels in heterogeneous systems of agents from multiple trajectories JMLR 2021 Learning to Select Exogenous Events for Marked Temporal Point Process NeurIPS 2021 Learning to Stop with Surprisingly Few Samples COLT 2021 Learning with User-Level Privacy NeurIPS 2021 Lenient Regret and Good-Action Identification in Gaussian Process Bandits ICML 2021 Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation NeurIPS 2021 LightGuardian: A Full-Visibility, Lightweight, In-band Telemetry System Using Sketchlets NSDI 2021 Linear Bandits on Uniformly Convex Sets JMLR 2021 Linear-Time Probabilistic Solution of Boundary Value Problems NeurIPS 2021 Locally differentially private estimation of functionals of discrete distributions NeurIPS 2021 LocalNewton: Reducing communication rounds for distributed learning UAI 2021 Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency AISTATS 2021 Lossless Compression of Efficient Private Local Randomizers ICML 2021