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Stochastic Processes

2,667 papers

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Papers

Large-Scale Gaussian Processes via Alternating Projection AISTATS 2024
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression AISTATS 2024
From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach AISTATS 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling AISTATS 2024
A Greedy Approximation for k-Determinantal Point Processes AISTATS 2024
Probabilistic Calibration by Design for Neural Network Regression AISTATS 2024
On Feynman-Kac training of partial Bayesian neural networks AISTATS 2024
Learning multivariate temporal point processes via the time-change theorem AISTATS 2024
Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training AISTATS 2024
From Data Imputation to Data Cleaning — Automated Cleaning of Tabular Data Improves Downstream Predictive Performance AISTATS 2024
Data-Driven Confidence Intervals with Optimal Rates for the Mean of Heavy-Tailed Distributions AISTATS 2024
Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression AISTATS 2024
Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks AISTATS 2024
Why is parameter averaging beneficial in SGD? An objective smoothing perspective AISTATS 2024
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles AISTATS 2024
Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization AISTATS 2024
An Analytic Solution to Covariance Propagation in Neural Networks AISTATS 2024
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements AISTATS 2024
First Passage Percolation with Queried Hints AISTATS 2024
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference AISTATS 2024
Probabilistic Modeling for Sequences of Sets in Continuous-Time AISTATS 2024
Soft-constrained Schrödinger Bridge: a Stochastic Control Approach AISTATS 2024
Coreset Markov chain Monte Carlo AISTATS 2024
Sample Efficient Learning of Factored Embeddings of Tensor Fields AISTATS 2024
autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm AISTATS 2024