We have 3 of 22 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Kernel-Complexity Edge Sanitization (KCES), a training-free and model-agnostic framework for defending against structural attacks, provides a principled and efficient framework for securing GNNs.
This work proposes ARMOR (Anchor Rollout and Mixed Optimization for RL), a framework that shifts the paradigm from passive penalty to active sample stabilization, enabling sustained performance improvements over extended training horizons.
This work proposes Experience-Augmented Policy Optimization (EAPO), which leverages a prior RL-optimized policy as an action-level experience prior and selectively injects experience at critical decision points during rollout to ensure stable and unbiased learning from experience-augmented rollouts.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
