Algorithm/Software

SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems
We design deep neural networks (DNNs) and corresponding networks’ splittings to distribute DNNs’ workload to camera sensors …
Xin Dong, Ziyun Li, Meng Li, Zhongnan Qu, Barbara De Salvo, Chiao Liu, Hsiang-Tsung Kung
Paper
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training
Designing accurate and efficient vision transformers (ViTs) is a highly important but challenging task. Supernet-based one-shot neural …
Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra
Paper
AlphaNet: Improved Training of Supernets with Alpha-Divergence
Weight-sharing neural architecture search (NAS) is an effective technique for automating efficient neural architecture design. …
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra
Paper
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling
An attentive sampling strategy that improves weight-sharing neural architecture search across a broad efficiency range.
Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra
Paper
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
Data augmentation (DA) is an essential technique for training state-of-the-art deep learning systems. In this paper, we empirically …
Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu
Paper
TimingSAT: Decamouflaging timing-based logic obfuscation
In order to counter advanced reverse engineering techniques, various integrated circuit (IC) camouflaging methods are proposed to …
Meng Li, Kaveh Shamsi, Yier Jin, David Z Pan
Paper
Federated Learning with Non-IID Data
Federated learning enables resource-constrained edge compute devices, such as mobile phones and IoT devices, to learn a shared model …
Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vikas Chandra
Paper
PrivyNet: A Flexible Framework for Privacy-Preserving Deep Neural Network Training
Massive data exist among user local platforms that usually cannot support deep neural network (DNN) training due to computation and …
Meng Li, Liangzhen Lai, Naveen Suda, Vikas Chandra, David Z. Pan
Paper
Cross-level monte carlo framework for system vulnerability evaluation against fault attack
Fault attack becomes a serious threat to system security and requires to be evaluated in the design stage. Existing methods usually …
Meng Li, Liangzhen Lai, Vikas Chandra, David Z. Pan
Paper
AppSAT: Approximately Deobfuscating Integrated Circuits
In today’s diversified semiconductor supply-chain, protecting intellectual property (IP) and maintaining manufacturing integrity …
Kaveh Shamsi, Meng Li, Travis Meade, Zheng Zhao, David Z Pan, Yier Jin
Paper