conftrace_
← Optimization
Mathematics & Optimization › Optimization ›

Stochastic Methods

2,788 papers

Papers per year

1
2
23
82
292
98
'00
'05
'10
'15
'20
'25

Papers

Stochastic continuous normalizing flows: training SDEs as ODEs UAI 2021
Probabilistic DAG search UAI 2021
Sum-product laws and efficient algorithms for imprecise Markov chains UAI 2021
Nearest neighbor search under uncertainty UAI 2021
Bias-corrected peaks-over-threshold estimation of the CVaR UAI 2021
Convergence behavior of belief propagation: estimating regions of attraction via Lyapunov functions UAI 2021
Doubly non-central beta matrix factorization for DNA methylation data UAI 2021
Efficient online inference for nonparametric mixture models UAI 2021
No-regret approximate inference via Bayesian optimisation UAI 2021
Geometric rates of convergence for kernel-based sampling algorithms UAI 2021
Fourier Sparse Leverage Scores and Approximate Kernel Learning NIPS 2020
Stein Self-Repulsive Dynamics: Benefits From Past Samples NIPS 2020
Generalised Bayesian Filtering via Sequential Monte Carlo NIPS 2020
The route to chaos in routing games: When is price of anarchy too optimistic? NIPS 2020
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization NIPS 2020
Coresets for Near-Convex Functions NIPS 2020
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits NIPS 2020
Projected Stein Variational Gradient Descent NIPS 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence NIPS 2020
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance NIPS 2020
Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function NIPS 2020
Dual Instrumental Variable Regression NIPS 2020
Finite Continuum-Armed Bandits NIPS 2020
Optimal Private Median Estimation under Minimal Distributional Assumptions NIPS 2020
Modeling Noisy Annotations for Crowd Counting NIPS 2020