2 citations · 2 across the 4 of their papers we have counts for
4 papers
KO: Kinetics-inspired Neural Optimizer with PDE Simulation Approaches
Mingquan Feng, Yixin Huang, Yifan Fu +2
The design of effective optimization algorithms for neural networks remains a fundamental challenge, and most existing methods rely on heuristic extensions of gradient-based update…
Not All Samples Should Be Utilized Equally: Towards Understanding and Improving Dataset Distillation
Shaobo Wang, Yantai Yang, Qilong Wang +3
Dataset Distillation (DD) aims to synthesize a small dataset capable of performing comparably to the original dataset. Despite the success of numerous DD methods, theoretical explo…
Think2Drive: Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving (in CARLA-v2)
Qifeng Li, Xiaosong Jia, Shaobo Wang +1
Real-world autonomous driving (AD) especially urban driving involves many corner cases. The lately released AD simulator CARLA v2 adds 39 common events in the driving scene, and pr…
Unified Batch Normalization: Identifying and Alleviating the Feature Condensation in Batch Normalization and a Unified Framework
Shaobo Wang, Xiangdong Zhang, Dongrui Liu +1
Batch Normalization (BN) has become an essential technique in contemporary neural network design, enhancing training stability. Specifically, BN employs centering and scaling opera…