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Stochastic Processes

2,667 papers

Papers per year

Papers

Communication-efficient SGD: From Local SGD to One-Shot Averaging NIPS 2021
Estimating High Order Gradients of the Data Distribution by Denoising NIPS 2021
A Max-Min Entropy Framework for Reinforcement Learning NIPS 2021
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds NIPS 2021
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD NIPS 2021
Generalized Linear Bandits with Local Differential Privacy NIPS 2021
Joint Inference for Neural Network Depth and Dropout Regularization NIPS 2021
Learning Generalized Gumbel-max Causal Mechanisms NIPS 2021
Stochastic Multi-Armed Bandits with Control Variates NIPS 2021
Permuton-induced Chinese Restaurant Process NIPS 2021
Robustness between the worst and average case NIPS 2021
Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity NIPS 2021
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks NIPS 2021
Adjusting for Autocorrelated Errors in Neural Networks for Time Series NIPS 2021
Deep Explicit Duration Switching Models for Time Series NIPS 2021
Batched Thompson Sampling NIPS 2021
Optimal Algorithms for Stochastic Contextual Preference Bandits NIPS 2021
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize NIPS 2021
Streaming Linear System Identification with Reverse Experience Replay NIPS 2021
Parallelised Diffeomorphic Sampling-based Motion Planning CORL 2021
Using Physics Knowledge for Learning Rigid-body Forward Dynamics with Gaussian Process Force Priors CORL 2021
Learning Density Distribution of Reachable States for Autonomous Systems CORL 2021
Orientation Probabilistic Movement Primitives on Riemannian Manifolds CORL 2021
Disposable Linear Bandits for Online Recommendations AAAI 2021
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks AAAI 2021