most citedTensorTEE: Unifying Heterogeneous TEE Granularity for Efficient Secure Collaborative Tensor Computing

12 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2024

HeteroMorpheus: Universal Control Based on Morphological Heterogeneity Modeling

YiFan Hao, Yang Yang, Junru Song +4

In the field of robotic control, designing individual controllers for each robot leads to high computational costs. Universal control policies, applicable across diverse robot morp…

cs.CR202412 cited

TensorTEE: Unifying Heterogeneous TEE Granularity for Efficient Secure Collaborative Tensor Computing

Husheng Han, Xinyao Zheng, Yuanbo Wen +11

Heterogeneous collaborative computing with NPU and CPU has received widespread attention due to its substantial performance benefits. To ensure data confidentiality and integrity d…

cs.LG2024

On the Benefits of Over-parameterization for Out-of-Distribution Generalization

Yifan Hao, Yong Lin, Difan Zou +1

In recent years, machine learning models have achieved success based on the independently and identically distributed assumption. However, this assumption can be easily violated in…

cs.AI2023

Emergent Communication for Rules Reasoning

Yuxuan Guo, Yifan Hao, Rui Zhang +14

Research on emergent communication between deep-learning-based agents has received extensive attention due to its inspiration for linguistics and artificial intelligence. However,…

cs.LG2023

Ultra-low Precision Multiplication-free Training for Deep Neural Networks

Chang Liu, Rui Zhang, Xishan Zhang +5

The training for deep neural networks (DNNs) demands immense energy consumption, which restricts the development of deep learning as well as increases carbon emissions. Thus, the s…