6.5k citations · 18.4k across the 52 of their papers we have counts for
5 papers · 1 filter
Training Kinetics in 15 Minutes: Large-scale Distributed Training on Videos
Ji Lin, Chuang Gan, Song Han
Deep video recognition is more computationally expensive than image recognition, especially on large-scale datasets like Kinetics [1]. Therefore, training scalability is essential…
Once-for-All: Train One Network and Specialize it for Efficient Deployment
Han Cai, Chuang Gan, Tianzhe Wang +2
We address the challenging problem of efficient inference across many devices and resource constraints, especially on edge devices. Conventional approaches either manually design o…
Point-Voxel CNN for Efficient 3D Deep Learning
Zhijian Liu, Haotian Tang, Yujun Lin +1
We present Point-Voxel CNN (PVCNN) for efficient, fast 3D deep learning. Previous work processes 3D data using either voxel-based or point-based NN models. However, both approaches…
Deep Leakage from Gradients
Ligeng Zhu, Zhijian Liu, Song Han
Exchanging gradients is a widely used method in modern multi-node machine learning system (e.g., distributed training, collaborative learning). For a long time, people believed tha…
Design Automation for Efficient Deep Learning Computing
Song Han, Han Cai, Ligeng Zhu +4
Efficient deep learning computing requires algorithm and hardware co-design to enable specialization: we usually need to change the algorithm to reduce memory footprint and improve…