Co-occurring keywords · papers mentioning both
Papers
Margin in Abstract Spaces
COLT 2026
Provably Data-Driven Projection Method for Quadratic Programming
AAAI 2026
Data-Driven Performance Guarantees for Classical and Learned Optimizers
JMLR 2025
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
ICML 2025
Learning Configurations for Data-Driven Multi-Objective Optimization
ICML 2025
Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation
JMLR 2025
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees
AISTATS 2025
Metric Learning in an RKHS
UAI 2025
Protein Fitness Landscape: Spectral Graph Theory Perspective
AISTATS 2025
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers
ICLR 2025
Public-data Assisted Private Stochastic Optimization: Power and Limitations
NeurIPS 2024
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
ICML 2024
Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees (Abstract Reprint)
AAAI 2024
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models
NeurIPS 2023
Generalization Guarantees of Self-Training of Halfspaces under Label Noise Corruption
IJCAI 2023
How Sharpness-Aware Minimization Minimizes Sharpness?
ICLR 2023
Implicit Balancing and Regularization: Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing
COLT 2023
Minimum Description Length and Generalization Guarantees for Representation Learning
NeurIPS 2023
Multi-Layer Neural Networks as Trainable Ladders of Hilbert Spaces
ICML 2023
On Proper Learnability between Average- and Worst-case Robustness
NeurIPS 2023
On the Generalization of Multi-modal Contrastive Learning
ICML 2023
PAC-Bayesian Learning of Optimization Algorithms
AISTATS 2023
Principled Approaches for Private Adaptation from a Public Source
AISTATS 2023
Rethinking Label Refurbishment: Model Robustness under Label Noise
AAAI 2023
Sample Boosting Algorithm (SamBA) - An interpretable greedy ensemble classifier based on local expertise for fat data
UAI 2023