Xue Lin

A Profit Optimization Framework of Energy Storage Devices in Data Centers: Hierarchical Structure and Hybrid Types

2016

This paper investigates the hierarchical deployment and over-provisioning of energy storage devices (ESDs) in data ceners by (i) adopting a realistic power delivery architecture (from Intel) for centralized ESD structure as the starting point, (ii) …

An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks

2018

Deep neural networks (DNNs) are known vulnerable to adversarial attacks. That is, adversarial examples, obtained by adding delicately crafted distortions onto original legal inputs, can mislead a DNN to classify them as any target labels. …

Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent

2020 · arXiv (Cornell University)

Despite the great achievements of the modern deep neural networks (DNNs), the vulnerability/robustness of state-of-the-art DNNs raises security concerns in many application domains requiring high reliability. Various adversarial attacks are proposed to sabotage the learning …

Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond

2020 · arXiv (Cornell University)

Linear relaxation based perturbation analysis (LiRPA) for neural networks, which computes provable linear bounds of output neurons given a certain amount of input perturbation, has become a core component in robustness verification and certified defense. …