Co-occurring keywords · papers mentioning both
Papers
Bridging the Theoretical Gap in Randomized Smoothing
AISTATS 2025
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
ICML 2025
Tight and Fast Bounds for Multi-Label Learning
ICML 2025
Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective
ICCV 2025
Achieving Domain-Independent Certified Robustness via Knowledge Continuity
NeurIPS 2024
CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning
ICLR 2024
Compressing Latent Space via Least Volume
ICLR 2024
Generalization Analysis for Multi-Label Learning
ICML 2024
Improve Robustness of Reinforcement Learning against Observation Perturbations via l∞ Lipschitz Policy Networks
AAAI 2024
Model-based Reinforcement Learning for Parameterized Action Spaces
ICML 2024
On the Distance from Calibration in Sequential Prediction
COLT 2024
Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures
AISTATS 2024
Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
ICML 2024
A graphon-signal analysis of graph neural networks
NeurIPS 2023
Beyond the Golden Ratio for Variational Inequality Algorithms
JMLR 2023
Certifying Ensembles: A General Certification Theory with S-Lipschitzness
ICML 2023
Differential Privacy has Bounded Impact on Fairness in Classification
ICML 2023
Efficient displacement convex optimization with particle gradient descent
ICML 2023
Generalization bounds for neural ordinary differential equations and deep residual networks
NeurIPS 2023
Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function
ICLR 2023
Learning Globally Smooth Functions on Manifolds
ICML 2023
LipsFormer: Introducing Lipschitz Continuity to Vision Transformers
ICLR 2023
Manifold-Preserving Transformers are Effective for Short-Long Range Encoding
EMNLP 2023
Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs
ICLR 2023
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms
NeurIPS 2023