error bound

To smooth a cloud or to pin it down: Expressiveness guarantees and insights on score matching in denoising diffusion models UAI 2024 Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy ICML 2024 When and How Does In-Distribution Label Help Out-of-Distribution Detection? ICML 2024 Which Is More Effective in Label Noise Cleaning, Correction or Filtering? AAAI 2024 A Bounded Ability Estimation for Computerized Adaptive Testing NeurIPS 2023 A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem AISTATS 2023 A General Theory of Correct, Incorrect, and Extrinsic Equivariance NeurIPS 2023 A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning NeurIPS 2023 (Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy NeurIPS 2023 Constant Matters: Fine-grained Error Bound on Differentially Private Continual Observation ICML 2023 Error Bounds for Learning with Vector-Valued Random Features NeurIPS 2023 Error Estimation for Random Fourier Features AISTATS 2023 Fast, Approximate Vector Queries on Very Large Unstructured Datasets NSDI 2023 Limitations on approximation by deep and shallow neural networks JMLR 2023 On the bias of K-fold cross validation with stable learners AISTATS 2023 Predictor-corrector algorithms for stochastic optimization under gradual distribution shift ICLR 2023 Residual-based error bound for physics-informed neural networks UAI 2023 Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation NeurIPS 2023 The Price of Differential Privacy under Continual Observation ICML 2023 A bounded-noise mechanism for differential privacy COLT 2022 A Hybrid Quantum-Classical Algorithm for Robust Fitting CVPR 2022 Beyond Sub-Gaussian Noises: Sharp Concentration Analysis for Stochastic Gradient Descent JMLR 2022 Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound NeurIPS 2022 Multiclass learning with margin: exponential rates with no bias-variance trade-off ICML 2022 On Low-rank Trace Regression under General Sampling Distribution JMLR 2022