Showing 1–20 of 53 results
/ Date/ Name
Dec 2, 2019KernelNet: A Data-Dependent Kernel Parameterization for Deep Generative ModelingFeb 7, 2021Meta-Learning with Neural Tangent KernelsOct 5, 2020Learning Manifold Implicitly via Explicit Heat-Kernel LearningOct 3, 2022On Stability and Generalization of Bilevel Optimization ProblemFeb 9, 2018Large Scale Constrained Linear Regression Revisited: Faster Algorithms via PreconditioningOct 16, 2024Truthful High Dimensional Sparse Linear RegressionFeb 22, 2025Towards User-level Private Reinforcement Learning with Human FeedbackSep 4, 2025Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise ConditionMay 15, 2020Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial RobustnessNov 27, 2021LAFITE: Towards Language-Free Training for Text-to-Image GenerationMay 10, 2021Learning High-Dimensional Distributions with Latent Neural Fokker-Planck KernelsOct 1, 2019Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled DataDec 7, 2021A Generic Approach for Enhancing GANs by Regularized Latent OptimizationApr 30, 2012Linear Time Algorithm for Projective ClusteringMay 27, 2024TopoLa: a novel embedding framework for understanding complex networksMay 27, 2024Understanding Forgetting in Continual Learning with Linear RegressionJan 14, 2025TopoLa: A Universal Framework to Enhance Cell Representations for Single-cell and Spatial Omics through Topology-encoded Latent Hyperbolic GeometryMar 8, 2025Nearly Optimal Differentially Private ReLU RegressionFeb 2, 2026Provable Effects of Data Replay in Continual Learning: A Feature Learning PerspectiveOct 21, 2020On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data