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Methodology
← Optimization & Theory
Machine Learning
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Optimization & Theory
›
Stochastic Processes
2667 directly classified papers
Papers per year
2003: 4
2004: 1
2005: 2
2006: 9
2007: 11
2008: 17
2009: 18
2010: 30
2011: 36
2012: 37
2013: 50
2014: 56
2015: 60
2016: 77
2017: 132
2018: 154
2019: 211
2020: 244
2021: 311
2022: 279
2023: 376
2024: 326
2025: 157
2026: 69
Papers
Posterior sampling strategies based on discretized stochastic differential equations for machine learning applications
JMLR 2020
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients
JMLR 2020
A Multi-Hypothesis Approach to Color Constancy
CVPR 2020
Correspondence-Free Material Reconstruction using Sparse Surface Constraints
CVPR 2020
Iterative Context-Aware Graph Inference for Visual Dialog
CVPR 2020
Generating Narrative Text in a Switching Dynamical System
CONLL 2020
Model and Reinforcement Learning for Markov Games with Risk Preferences
AAAI 2020
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
ICML 2020
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference
ICML 2020
Forecasting Sequential Data Using Consistent Koopman Autoencoders
ICML 2020
Why bigger is not always better: on finite and infinite neural networks
ICML 2020
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy
AAAI 2020
Localizing and Amortizing: Efficient Inference for Gaussian Processes
ACML 2020
Cooperative Multi-Agent Bandits with Heavy Tails
ICML 2020
Online Robust Regression via SGD on the l1 loss
NIPS 2020
Stochastic Flows and Geometric Optimization on the Orthogonal Group
ICML 2020
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model
NIPS 2020
Modelling Lexical Ambiguity with Density Matrices
EMNLP 2020
Localized Learning of Robust Controllers for Networked Systems with Dynamic Topology
L4DC 2020
DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs
IJCAI 2020
On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics
JMLR 2020
Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement
JMLR 2020
Risk Bounds for Reservoir Computing
JMLR 2020
Training for Gibbs Sampling on Conditional Random Fields with Neural Scoring Factors
EMNLP 2020
Online matrix factorization for Markovian data and applications to Network Dictionary Learning
JMLR 2020
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