activity
20172021
most citedExploring the Regularity of Sparse Structure in Convolutional Neural Networks

230 citations · 232 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2025

QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs

Wei Huang, Yi Ge, Shuai Yang +11

We propose QeRL, a Quantization-enhanced Reinforcement Learning framework for large language models (LLMs). While RL is essential for LLMs' reasoning capabilities, it is resource-i…

cs.CV20212 cited

PatchNet -- Short-range Template Matching for Efficient Video Processing

Huizi Mao, Sibo Zhu, Song Han +1

Object recognition is a fundamental problem in many video processing tasks, accurately locating seen objects at low computation cost paves the way for on-device video recognition.…

cs.CV2019

A Delay Metric for Video Object Detection: What Average Precision Fails to Tell

Huizi Mao, Xiaodong Yang, William J. Dally

Average precision (AP) is a widely used metric to evaluate detection accuracy of image and video object detectors. In this paper, we analyze object detection from videos and point…

cs.CV2018

CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video

Huizi Mao, Taeyoung Kong, William J. Dally

Detecting objects in a video is a compute-intensive task. In this paper we propose CaTDet, a system to speedup object detection by leveraging the temporal correlation in video. CaT…

cs.LG2017230 cited

Exploring the Regularity of Sparse Structure in Convolutional Neural Networks

Huizi Mao, Song Han, Jeff Pool +4

Sparsity helps reduce the computational complexity of deep neural networks by skipping zeros. Taking advantage of sparsity is listed as a high priority in next generation DNN accel…