research
∙
06/07/2023
Professional Basketball Player Behavior Synthesis via Planning with Diffusion
Dynamically planning in multi-agent systems has been explored to improve...
share
research
∙
11/01/2022
DensePure: Understanding Diffusion Models towards Adversarial Robustness
Diffusion models have been recently employed to improve certified robust...
research
∙
09/27/2021
Structural Stability of a Family of Group Formation Games
We introduce and study a group formation game in which individuals/agent...
research
∙
06/17/2021
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
In Autonomous Driving (AD) systems, perception is both security and safe...
research
∙
05/04/2021
Aggregate Cyber-Risk Management in the IoT Age: Cautionary Statistics for (Re)Insurers and Likes
In this paper, we provide (i) a rigorous general theory to elicit condit...
research
∙
03/25/2021
Multi-planner intervention in network games with community structures
Network games study the strategic interaction of agents connected throug...
research
∙
01/20/2021
Multi-Scale Games: Representing and Solving Games on Networks with Group Structure
Network games provide a natural machinery to compactly represent strateg...
research
∙
10/21/2020
How Do Fair Decisions Fare in Long-term Qualification?
Although many fairness criteria have been proposed for decision making, ...
research
∙
01/14/2020
Fairness in Learning-Based Sequential Decision Algorithms: A Survey
Algorithmic fairness in decision-making has been studied extensively in ...
research
∙
10/08/2019
Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms
Alternating direction method of multiplier (ADMM) is a powerful method t...
research
∙
07/11/2019
Adversarial Objects Against LiDAR-Based Autonomous Driving Systems
Deep neural networks (DNNs) are found to be vulnerable against adversari...
research
∙
05/02/2019
Long term impact of fair machine learning in sequential decision making: representation disparity and group retention
Machine learning models trained on data from multiple demographic groups...
research
∙
11/19/2018
Distributed Learning of Average Belief Over Networks Using Sequential Observations
This paper addresses the problem of distributed learning of average beli...
research
∙
10/11/2018
Realistic Adversarial Examples in 3D Meshes
Highly expressive models such as deep neural networks (DNNs) have been w...
research
∙
10/11/2018
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
Deep Neural Networks (DNNs) have been widely applied in various recognit...
research
∙
10/07/2018
Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms
Alternating direction method of multiplier (ADMM) is a powerful method t...
research
∙
06/06/2018
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Alternating direction method of multiplier (ADMM) is a popular method us...
research
∙
01/08/2018
Spatially transformed adversarial examples
Recent studies show that widely used deep neural networks (DNNs) are vul...
research
∙
01/08/2018
Generating adversarial examples with adversarial networks
Deep neural networks (DNNs) have been found to be vulnerable to adversar...
research
∙
05/15/2013
