124 citations · 187 across the 8 of their papers we have counts for
8 papers
Transition Role of Entangled Data in Quantum Machine Learning
Xinbiao Wang, Yuxuan Du, Zhuozhuo Tu +3
Entanglement serves as the resource to empower quantum computing. Recent progress has highlighted its positive impact on learning quantum dynamics, wherein the integration of entan…
Power of Quantum Generative Learning
Yuxuan Du, Zhuozhuo Tu, Bujiao Wu +2
The intrinsic probabilistic nature of quantum mechanics invokes endeavors of designing quantum generative learning models (QGLMs). Despite the empirical achievements, the foundatio…
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer
Shiye Lei, Zhuozhuo Tu, Leszek Rutkowski +4
Bayesian neural networks (BNNs) have become a principal approach to alleviate overconfident predictions in deep learning, but they often suffer from scaling issues due to a large n…
Few-shot Backdoor Defense Using Shapley Estimation
Jiyang Guan, Zhuozhuo Tu, Ran He +1
Deep neural networks have achieved impressive performance in a variety of tasks over the last decade, such as autonomous driving, face recognition, and medical diagnosis. However,…
Efficient measure for the expressivity of variational quantum algorithms
Yuxuan Du, Zhuozhuo Tu, Xiao Yuan +1
The superiority of variational quantum algorithms (VQAs) such as quantum neural networks (QNNs) and variational quantum eigen-solvers (VQEs) heavily depends on the expressivity of…
Stretchable Cells Help DARTS Search Better
Tao Huang, Shan You, Yibo Yang +4
Differentiable neural architecture search (DARTS) has gained much success in discovering flexible and diverse cell types. To reduce the evaluation gap, the supernet is expected to…
Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model
Gemeng Zhang, Aiying Zhang, Biao Cai +3
Functional connectivity (FC) has been widely used to study brain network interactions underlying the emerging cognition and behavior of an individual. FC is usually defined as the…
Theoretical Analysis of Adversarial Learning: A Minimax Approach
Zhuozhuo Tu, Jingwei Zhang, Dacheng Tao
Here we propose a general theoretical method for analyzing the risk bound in the presence of adversaries. Specifically, we try to fit the adversarial learning problem into the mini…