1.8k citations · 2.3k across the 57 of their papers we have counts for
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Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework
Pranay Sharma, Kaidi Xu, Sijia Liu +3
In this work, we focus on the study of stochastic zeroth-order (ZO) optimization which does not require first-order gradient information and uses only function evaluations. The pro…
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel +3
A trade-off between accuracy and fairness is almost taken as a given in the existing literature on fairness in machine learning. Yet, it is not preordained that accuracy should dec…
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen +2
Verifying robustness of neural network classifiers has attracted great interests and attention due to the success of deep neural networks and their unexpected vulnerability to adve…
Is Ordered Weighted Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR
Pin-Yu Chen, Bhanukiran Vinzamuri, Sijia Liu
Many state-of-the-art machine learning models such as deep neural networks have recently shown to be vulnerable to adversarial perturbations, especially in classification tasks. Mo…
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications
Pin-Yu Chen, Lingfei Wu, Sijia Liu +1
The von Neumann graph entropy (VNGE) facilitates measurement of information divergence and distance between graphs in a graph sequence. It has been successfully applied to various…
On the Supermodularity of Active Graph-based Semi-supervised Learning with Stieltjes Matrix Regularization
Pin-Yu Chen, Dennis Wei
Active graph-based semi-supervised learning (AG-SSL) aims to select a small set of labeled examples and utilize their graph-based relation to other unlabeled examples to aid in mac…