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Stochastic Processes

2667 directly classified papers

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Papers

Reducing the variance in online optimization by transporting past gradients NIPS 2019
Differentially Private Markov Chain Monte Carlo NIPS 2019
Amortized Monte Carlo Integration ICML 2019
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates NIPS 2019
Stochastic Canonical Correlation Analysis JMLR 2019
Quantifying Uncertainty in Online Regression Forests JMLR 2019
Hamiltonian Monte Carlo with Energy Conserving Subsampling JMLR 2019
No-Regret Bayesian Optimization with Unknown Hyperparameters JMLR 2019
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations JMLR 2019
Iterated Learning in Dynamic Social Networks JMLR 2019
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme COLT 2019
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning ICML 2019
On Model Stability as a Function of Random Seed CONLL 2019
Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes IJCAI 2019
Learning Deep Stochastic Optimal Control Policies Using Forward-Backward SDEs RSS 2019
Nonlinear Distributional Gradient Temporal-Difference Learning ICML 2019
A Variational EM Framework With Adaptive Edge Selection for Blind Motion Deblurring CVPR 2019
Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization under Uncertainty IJCAI 2019
Joint Manifold Diffusion for Combining Predictions on Decoupled Observations CVPR 2019
Average-case Analysis of the Assignment Problem with Independent Preferences IJCAI 2019
MRI k-Space Motion Artefact Augmentation: Model Robustness and Task-Specific Uncertainty MIDL 2019
Learning to Explore Intrinsic Saliency for Stereoscopic Video CVPR 2019
PointFlow: 3D Point Cloud Generation With Continuous Normalizing Flows ICCV 2019
BOCK : Bayesian Optimization with Cylindrical Kernels ICML 2018
Transformation Autoregressive Networks ICML 2018