conftrace_
← Mathematics & Optimization
Mathematics & Optimization ›

Probability

519 papers (95 classified directly here)

Subtopics

Stochastic Processes (438)

Papers per year

10
9
30
19
'10
'15
'20
'25

Papers (including subtopics)

Three rates of convergence or separation via U-statistics in a dependent framework JMLR 2022
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint JMLR 2022
Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets JMLR 2022
Mappings for Marginal Probabilities with Applications to Models in Statistical Physics JMLR 2022
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling JMLR 2022
Convergence Rates for Gaussian Mixtures of Experts JMLR 2022
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence JMLR 2022
Interval-censored Hawkes processes JMLR 2022
Optimal prediction of Markov chains with and without spectral gap NIPS 2021
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification NIPS 2021
A Central Limit Theorem for Differentially Private Query Answering NIPS 2021
Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions NIPS 2021
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics NIPS 2021
Optimal Underdamped Langevin MCMC Method NIPS 2021
Relaxed Clustered Hawkes Process for Student Procrastination Modeling in MOOCs AAAI 2021
Loop Estimator for Discounted Values in Markov Reward Processes AAAI 2021
UNIPoint: Universally Approximating Point Processes Intensities AAAI 2021
The Influence of Memory in Multi-Agent Consensus AAAI 2021
Bounding Causal Effects on Continuous Outcome AAAI 2021
Reinforcement Learning in Parametric MDPs with Exponential Families AISTATS 2021
Rao-Blackwellised parallel MCMC AISTATS 2021
Calibrated Adaptive Probabilistic ODE Solvers AISTATS 2021
Couplings for Multinomial Hamiltonian Monte Carlo AISTATS 2021
An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo AISTATS 2021
Learning in Matrix Games can be Arbitrarily Complex COLT 2021