Co-occurring keywords · papers mentioning both
Papers
Towards Improved Risk Bounds for Transductive Learning
IJCAI 2025
Trajectory-Dependent Generalization Bounds for Pairwise Learning with φ-mixing Samples
IJCAI 2025
Universal generalization guarantees for Wasserstein distributionally robust models
ICLR 2025
A Closer Look at Curriculum Adversarial Training: From an Online Perspective
AAAI 2024
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression
NeurIPS 2024
Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
ICML 2024
A path-norm toolkit for modern networks: consequences, promises and challenges
ICLR 2024
Asymmetry in Low-Rank Adapters of Foundation Models
ICML 2024
A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples
ICML 2024
Bridging the Gap: Rademacher Complexity in Robust and Standard Generalization
COLT 2024
Classification with Deep Neural Networks and Logistic Loss
JMLR 2024
Comparing Comparators in Generalization Bounds
AISTATS 2024
Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond
NeurIPS 2024
Confidence-aware Contrastive Learning for Selective Classification
ICML 2024
Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound
NeurIPS 2024
Convolutional Spectral Kernel Learning with Generalization Guarantees (Abstract Reprint)
AAAI 2024
Fairness without Harm: An Influence-Guided Active Sampling Approach
NeurIPS 2024
Fair Off-Policy Learning from Observational Data
ICML 2024
Fantastic Generalization Measures are Nowhere to be Found
ICLR 2024
Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random
NeurIPS 2024
From Generalization Analysis to Optimization Designs for State Space Models
ICML 2024
Functions with average smoothness: structure, algorithms, and learning
JMLR 2024
Generalization Analysis for Label-Specific Representation Learning
NeurIPS 2024
Generalization Analysis for Multi-Label Learning
ICML 2024
Generalization Analysis of Machine Learning Algorithms via the Worst-Case Data-Generating Probability Measure
AAAI 2024