4 papers
Elucidating Representation Degradation Problem in Diffusion Model Training
Zhipeng Yao, Dazhou Li, Zitong Zhang +6
Diffusion models have achieved remarkable success, yet their training remains inefficient due to a severe optimization bottleneck, which we term Representation Degradation. As nois…
Dynamic Momentum Recalibration in Online Gradient Learning
Zhipeng Yao, Rui Yu, Guisong Chang +3
Stochastic Gradient Descent (SGD) and its momentum variants form the backbone of deep learning optimization, yet the underlying dynamics of their gradient behavior remain insuffici…
Signal Processing Meets SGD: From Momentum to Filter
Zhipeng Yao, Rui Yu, Guisong Chang +3
In deep learning, stochastic gradient descent (SGD) and its momentum-based variants are widely used for optimization. However, the internal dynamics of these methods remain underex…
UDQL: Bridging The Gap between MSE Loss and The Optimal Value Function in Offline Reinforcement Learning
Yu Zhang, Rui Yu, Zhipeng Yao +3
The Mean Square Error (MSE) is commonly utilized to estimate the solution of the optimal value function in the vast majority of offline reinforcement learning (RL) models and has a…