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cs.LG2025
Improving Compositional Generation with Diffusion Models Using Lift Scores
Chenning Yu, Sicun Gao
We introduce a novel resampling criterion using lift scores, for improving compositional generation in diffusion models. By leveraging the lift scores, we evaluate whether generate…
cs.LG2024
Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
Chung-En Sun, Sicun Gao, Tsui-Wei Weng
Robustness remains a paramount concern in deep reinforcement learning (DRL), with randomized smoothing emerging as a key technique for enhancing this attribute. However, a notable…
cs.LG2024★ 1 cited
Activation-Descent Regularization for Input Optimization of ReLU Networks
Hongzhan Yu, Sicun Gao
We present a new approach for input optimization of ReLU networks that explicitly takes into account the effect of changes in activation patterns. We analyze local optimization ste…