Stochastic Methods

A Provably Accurate Randomized Sampling Algorithm for Logistic Regression AAAI 2024 A Score-Based Deterministic Diffusion Algorithm with Smooth Scores for General Distributions AAAI 2024 A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers NeurIPS 2024 AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms AISTATS 2024 autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm AISTATS 2024 Bandits with Concave Aggregated Reward IJCAI 2024 Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training NeurIPS 2024 Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences NeurIPS 2024 Certified Machine Unlearning via Noisy Stochastic Gradient Descent NeurIPS 2024 Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine Learning CVPR 2024 Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization COLT 2024 Colored Noise in PPO: Improved Exploration and Performance through Correlated Action Sampling AAAI 2024 Common Diffusion Noise Schedules and Sample Steps Are Flawed WACV 2024 Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise NeurIPS 2024 Convergence of Kinetic Langevin Monte Carlo on Lie groups COLT 2024 Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games AISTATS 2024 Coreset Markov chain Monte Carlo AISTATS 2024 Correction to "Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations" JMLR 2024 Decentralized Noncooperative Games with Coupled Decision-Dependent Distributions NeurIPS 2024 Deep Learning for Computing Convergence Rates of Markov Chains NeurIPS 2024 Differentially Private Optimization with Sparse Gradients NeurIPS 2024 Differential Privacy in Scalable General Kernel Learning via K-means Nystr\"om Random Features NeurIPS 2024 Discerning Temporal Difference Learning AAAI 2024 DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling AAAI 2024 Distributionally Robust Optimization with Bias and Variance Reduction ICLR 2024