Zifan Wang | DeepAI

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293 publications
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Michael M. Zavlanos
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Karl H. Johansson
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Matt Fredrikson
29 publications

∙ 09/01/2023

Convergence Analysis of the Best Response Algorithm for Time-Varying Games

This paper studies a class of strongly monotone games involving non-coop...

0 Zifan Wang, et al. ∙

∙ 07/27/2023

Universal and Transferable Adversarial Attacks on Aligned Language Models

Because "out-of-the-box" large language models are capable of generating...

0 Andy Zou, et al. ∙

∙ 03/23/2023

Policy Evaluation in Distributional LQR

Distributional reinforcement learning (DRL) enhances the understanding o...

0 Zifan Wang, et al. ∙

∙ 03/08/2023

Streaming Kernel PCA Algorithm With Small Space

Principal Component Analysis (PCA) is a widely used technique in machine...

0 Yichuan Deng, et al. ∙

∙ 01/29/2023

Scaling in Depth: Unlocking Robustness Certification on ImageNet

Notwithstanding the promise of Lipschitz-based approaches to determinist...

0 Kai Hu, et al. ∙

∙ 01/26/2023

Learning Modulo Theories

Recent techniques that integrate solver layers into Deep Neural Networks...

8 Matt Fredrikson, et al. ∙

∙ 11/22/2022

Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization

Recent research in robust optimization has shown an overfitting-like phe...

0 Zifan Wang, et al. ∙

∙ 09/06/2022

A Zeroth-Order Momentum Method for Risk-Averse Online Convex Games

We consider risk-averse learning in repeated unknown games where the goa...

0 Zifan Wang, et al. ∙

∙ 06/01/2022

On the Perils of Cascading Robust Classifiers

Ensembling certifiably robust neural networks has been shown to be a pro...

0 Ravi Mangal, et al. ∙

∙ 05/24/2022

Faithful Explanations for Deep Graph Models

This paper studies faithful explanations for Graph Neural Networks (GNNs...

1 Zifan Wang, et al. ∙

∙ 03/16/2022

Risk-Averse No-Regret Learning in Online Convex Games

We consider an online stochastic game with risk-averse agents whose goal...

0 Zifan Wang, et al. ∙

∙ 01/29/2022

On Optimizing Shared-ride Mobility Services with Walking Legs

Shared-ride mobility services that incorporate traveler walking legs aim...

0 Zifan Wang, et al. ∙

∙ 10/06/2021

Consistent Counterfactuals for Deep Models

Counterfactual examples are one of the most commonly-cited methods for e...

0 Emily Black, et al. ∙

∙ 03/20/2021

Boundary Attributions Provide Normal (Vector) Explanations

Recent work on explaining Deep Neural Networks (DNNs) focuses on attribu...

8 Zifan Wang, et al. ∙

∙ 02/16/2021

Globally-Robust Neural Networks

The threat of adversarial examples has motivated work on training certif...

14 Klas Leino, et al. ∙

∙ 11/02/2020

Abstracting Influence Paths for Explaining (Contextualization of) BERT Models

While "attention is all you need" may be proving true, we do not yet kno...

0 Kaiji Lu, et al. ∙

∙ 09/17/2020

Towards Behavior-Level Explanation for Deep Reinforcement Learning

While Deep Neural Networks (DNNs) are becoming the state-of-the-art for ...

23 Xuan Chen, et al. ∙

∙ 06/11/2020

Smoothed Geometry for Robust Attribution

Feature attributions are a popular tool for explaining the behavior of D...

6 Zifan Wang, et al. ∙

∙ 05/20/2020

Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks

Recently, increasing attention has been drawn to the internal mechani...

0 Zifan Wang, et al. ∙

∙ 05/06/2020

Towards Frequency-Based Explanation for Robust CNN

Current explanation techniques towards a transparent Convolutional Neura...

0 Zifan Wang, et al. ∙

∙ 02/19/2020

Interpreting Interpretations: Organizing Attribution Methods by Criteria

Attribution methods that explains the behaviour of machine learning mode...

0 Zifan Wang, et al. ∙

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