885 citations · 1.7k across the 71 of their papers we have counts for
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Generalized Likelihood Ratio Test for Adversarially Robust Hypothesis Testing
Bhagyashree Puranik, Upamanyu Madhow, Ramtin Pedarsani
Machine learning models are known to be susceptible to adversarial attacks which can cause misclassification by introducing small but well designed perturbations. In this paper, we…
Towards Learning Generalizable Driving Policies from Restricted Latent Representations
Behrad Toghi, Rodolfo Valiente, Ramtin Pedarsani +1
Training intelligent agents that can drive autonomously in various urban and highway scenarios has been a hot topic in the robotics society within the last decades. However, the di…
Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic
Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh +2
With the adoption of autonomous vehicles on our roads, we will witness a mixed-autonomy environment where autonomous and human-driven vehicles must learn to co-exist by sharing the…
Cooperative Autonomous Vehicles that Sympathize with Human Drivers
Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh +2
Widespread adoption of autonomous vehicles will not become a reality until solutions are developed that enable these intelligent agents to co-exist with humans. This includes safel…
Social Coordination and Altruism in Autonomous Driving
Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh +2
Despite the advances in the autonomous driving domain, autonomous vehicles (AVs) are still inefficient and limited in terms of cooperating with each other or coordinating with vehi…
Emergent Prosociality in Multi-Agent Games Through Gifting
Woodrow Z. Wang, Mark Beliaev, Erdem Bıyık +3
Coordination is often critical to forming prosocial behaviors -- behaviors that increase the overall sum of rewards received by all agents in a multi-agent game. However, state of…
Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy
Erdem Bıyık, Daniel A. Lazar, Ramtin Pedarsani +1
Traffic congestion has large economic and social costs. The introduction of autonomous vehicles can potentially reduce this congestion by increasing road capacity via vehicle plato…
Robust Classification Under Attack for the Gaussian Mixture Model
Payam Delgosha, Hamed Hassani, Ramtin Pedarsani
It is well-known that machine learning models are vulnerable to small but cleverly-designed adversarial perturbations that can cause misclassification. While there has been major p…
Congestion-aware Bi-modal Delivery Systems Utilizing Drones
Mark Beliaev, Negar Mehr, Ramtin Pedarsani
Bi-modal delivery systems are a promising solution to the challenges posed by the increasing demand of e-commerce. Due to the potential benefit drones can have on logistics network…
The Role of Differentiation in Tolling of Traffic Networks with Mixed Autonomy
Daniel A. Lazar, Ramtin Pedarsani
With autonomous vehicles now sharing roads with human drivers, the era of mixed autonomy brings new challenges in dealing with congestion. One cause of congestion is when vehicle u…