conftrace_

error bound

88 papers

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convex optimization (1321) learning theory (519) kernel methods (1097) neural network (6616) convergence rate (607) classification error (38) active learning (1301) finite sample bound (12) lower bound (173) iteration complexity (70)

Papers

A Scalable and Exact Relaxation for Densest k-Subgraph via Error Bounds AAAI 2026
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities JMLR 2025
Sampling and Estimation on Manifolds using the Langevin Diffusion JMLR 2025
How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences JMLR 2025
Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective ICCV 2025
Error Bounds for Gaussian Process Regression Under Bounded Support Noise with Applications to Safety Certification AAAI 2025
Revisiting Sampson Approximations for Geometric Estimation Problems CVPR 2024
Error bounds, PL condition, and quadratic growth for weakly convex functions, and linear convergences of proximal point methods L4DC 2024
Error bounds for any regression model using Gaussian processes with gradient information AISTATS 2024
Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees AAAI 2024
An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization NIPS 2024
Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization NIPS 2024
Which Is More Effective in Label Noise Cleaning, Correction or Filtering? AAAI 2024
A Bounded Ability Estimation for Computerized Adaptive Testing NIPS 2023
Error Estimation for Random Fourier Features AISTATS 2023
Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation NIPS 2023
The Price of Differential Privacy under Continual Observation ICML 2023
A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning NIPS 2023
Error Bounds for Learning with Vector-Valued Random Features NIPS 2023
Constant Matters: Fine-grained Error Bound on Differentially Private Continual Observation ICML 2023
A General Theory of Correct, Incorrect, and Extrinsic Equivariance NIPS 2023
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy NIPS 2023
On the bias of K-fold cross validation with stable learners AISTATS 2023
A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem AISTATS 2023
Fast, Approximate Vector Queries on Very Large Unstructured Datasets NSDI 2023