research
∙
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...
share
research
∙
07/27/2023
Universal and Transferable Adversarial Attacks on Aligned Language Models
Because "out-of-the-box" large language models are capable of generating...
research
∙
03/23/2023
Policy Evaluation in Distributional LQR
Distributional reinforcement learning (DRL) enhances the understanding o...
research
∙
03/08/2023
Streaming Kernel PCA Algorithm With Small Space
Principal Component Analysis (PCA) is a widely used technique in machine...
research
∙
01/29/2023
Scaling in Depth: Unlocking Robustness Certification on ImageNet
Notwithstanding the promise of Lipschitz-based approaches to determinist...
research
∙
01/26/2023
Learning Modulo Theories
Recent techniques that integrate solver layers into Deep Neural Networks...
research
∙
11/22/2022
Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization
Recent research in robust optimization has shown an overfitting-like phe...
research
∙
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...
research
∙
06/01/2022
On the Perils of Cascading Robust Classifiers
Ensembling certifiably robust neural networks has been shown to be a pro...
research
∙
05/24/2022
Faithful Explanations for Deep Graph Models
This paper studies faithful explanations for Graph Neural Networks (GNNs...
research
∙
03/16/2022
Risk-Averse No-Regret Learning in Online Convex Games
We consider an online stochastic game with risk-averse agents whose goal...
research
∙
01/29/2022
On Optimizing Shared-ride Mobility Services with Walking Legs
Shared-ride mobility services that incorporate traveler walking legs aim...
research
∙
10/06/2021
Consistent Counterfactuals for Deep Models
Counterfactual examples are one of the most commonly-cited methods for e...
research
∙
03/20/2021
Boundary Attributions Provide Normal (Vector) Explanations
Recent work on explaining Deep Neural Networks (DNNs) focuses on attribu...
research
∙
02/16/2021
Globally-Robust Neural Networks
The threat of adversarial examples has motivated work on training certif...
research
∙
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...
research
∙
09/17/2020
Towards Behavior-Level Explanation for Deep Reinforcement Learning
While Deep Neural Networks (DNNs) are becoming the state-of-the-art for ...
research
∙
06/11/2020
Smoothed Geometry for Robust Attribution
Feature attributions are a popular tool for explaining the behavior of D...
research
∙
05/20/2020
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks
Recently, increasing attention has been drawn to the internal mechani...
research
∙
05/06/2020
Towards Frequency-Based Explanation for Robust CNN
Current explanation techniques towards a transparent Convolutional Neura...
research
∙
02/19/2020