S. Shankar Sastry

research

∙ 03/04/2022

DEC-LOS-RRT: Decentralized Path Planning for Multi-robot Systems with Line-of-sight Constrained Communication

Decentralized planning for multi-agent systems, such as fleets of robots...

0 Victoria Tuck, et al. ∙

research

∙ 06/23/2021

Who Leads and Who Follows in Strategic Classification?

As predictive models are deployed into the real world, they must increas...

9 Tijana Zrnic, et al. ∙

research

∙ 06/16/2021

Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization

Min-max optimization is emerging as a key framework for analyzing proble...

5 Chinmay Maheshwari, et al. ∙

research

∙ 03/27/2021

On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective

The widespread adoption of nonlinear Receding Horizon Control (RHC) stra...

13 Tyler Westenbroek, et al. ∙

research

∙ 02/24/2021

Maximum Likelihood Constraint Inference from Stochastic Demonstrations

When an expert operates a perilous dynamic system, ideal constraint info...

12 David L. McPherson, et al. ∙

research

∙ 10/26/2020

Expert Selection in High-Dimensional Markov Decision Processes

In this work we present a multi-armed bandit framework for online expert...

8 Vicenc Rubies Royo, et al. ∙

research

∙ 04/15/2020

Improving Input-Output Linearizing Controllers for Bipedal Robots via Reinforcement Learning

The main drawbacks of input-output linearizing controllers are the need ...

0 Fernando Castañeda, et al. ∙

research

∙ 04/06/2020

Technical Report: Adaptive Control for Linearizable Systems Using On-Policy Reinforcement Learning

This paper proposes a framework for adaptively learning a feedback linea...

5 Tyler Westenbroek, et al. ∙

research

∙ 04/01/2020

Exponentially Stable First Order Control on Matrix Lie Groups

We present a novel first order controller for systems evolving on matrix...

0 Valmik Prabhu, et al. ∙

research

∙ 01/13/2020

LESS is More: Rethinking Probabilistic Models of Human Behavior

Robots need models of human behavior for both inferring human goals and ...

45 Andreea Bobu, et al. ∙

research

∙ 11/04/2019

Persistency of Excitation for Robustness of Neural Networks

When an online learning algorithm is used to estimate the unknown parame...

12 Kamil Nar, et al. ∙

research

∙ 10/29/2019

Feedback Linearization for Unknown Systems via Reinforcement Learning

We present a novel approach to control design for nonlinear systems, whi...

1 Tyler Westenbroek, et al. ∙

research

∙ 09/12/2019

Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning

While most approaches to the problem of Inverse Reinforcement Learning (...

41 Dexter R. R. Scobee, et al. ∙

research

∙ 07/08/2019

Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings

We show by counterexample that policy-gradient algorithms have no guaran...

1 Eric Mazumdar, et al. ∙

research

∙ 04/29/2019

Competitive Statistical Estimation with Strategic Data Sources

In recent years, data has played an increasingly important role in the e...

12 Tyler Westenbroek, et al. ∙

research

∙ 01/24/2019

Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples

State-of-the-art neural networks are vulnerable to adversarial examples;...

10 Kamil Nar, et al. ∙

research

∙ 01/03/2019

On Finding Local Nash Equilibria (and Only Local Nash Equilibria) in Zero-Sum Games

We propose a two-timescale algorithm for finding local Nash equilibria i...

0 Eric V. Mazumdar, et al. ∙

research

∙ 10/13/2018

Hierarchical Game-Theoretic Planning for Autonomous Vehicles

The actions of an autonomous vehicle on the road affect and are affected...

0 Jaime F. Fisac, et al. ∙

research

∙ 05/22/2018

Step Size Matters in Deep Learning

Training a neural network with the gradient descent algorithm gives rise...

0 Kamil Nar, et al. ∙

research

∙ 05/09/2018

Modeling Supervisor Safe Sets for Improving Collaboration in Human-Robot Teams

When a human supervisor collaborates with a team of robots, their attent...

0 David L. McPherson, et al. ∙

research

∙ 02/14/2018

Generating Plans that Predict Themselves

Collaboration requires coordination, and we coordinate by anticipating o...

0 Jaime F. Fisac, et al. ∙

research

∙ 02/06/2018

Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration

The study of human-robot interaction is fundamental to the design and us...

0 Chang Liu, et al. ∙

research

∙ 11/03/2017

People as Sensors: Imputing Maps from Human Actions

Despite growing attention in autonomy, there are still many open problem...

0 Oladapo Afolabi, et al. ∙

research

∙ 07/20/2017

Pragmatic-Pedagogic Value Alignment

For an autonomous system to provide value (e.g., to customers, designers...

0 Jaime F. Fisac, et al. ∙

research

∙ 06/27/2016

Towards Verified Artificial Intelligence

Verified artificial intelligence (AI) is the goal of designing AI-based ...

0 Sanjit A. Seshia, et al. ∙

research

∙ 07/25/2014

Dissimilarity-based Sparse Subset Selection

Finding an informative subset of a large collection of data points or mo...

0 Ehsan Elhamifar, et al. ∙

research

∙ 02/08/2014

Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment

Single-sample face recognition is one of the most challenging problems i...

0 Liansheng Zhuang, et al. ∙

research

∙ 12/07/2013

Robust Subspace System Identification via Weighted Nuclear Norm Optimization

Subspace identification is a classical and very well studied problem in ...

0 Dorsa Sadigh, et al. ∙

research

∙ 03/20/2013

Compressive Shift Retrieval

The classical shift retrieval problem considers two signals in vector fo...

0 Henrik Ohlsson, et al. ∙

research

∙ 01/29/2013

Quadratic Basis Pursuit

In many compressive sensing problems today, the relationship between the...

0 Henrik Ohlsson, et al. ∙

research

∙ 01/18/2012

On the Lagrangian Biduality of Sparsity Minimization Problems

Recent results in Compressive Sensing have shown that, under certain con...

0 Dheeraj Singaraju, et al. ∙

research

∙ 07/21/2010

Fast L1-Minimization Algorithms For Robust Face Recognition

L1-minimization refers to finding the minimum L1-norm solution to an und...

0 Allen Y. Yang, et al. ∙

S. Shankar Sastry

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