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05/15/2023
Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs
In numerous robotics and mechanical engineering applications, among othe...
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02/02/2023
Stochastic Contextual Bandits with Long Horizon Rewards
The growing interest in complex decision-making and language modeling pr...
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05/12/2022
Representation Learning for Context-Dependent Decision-Making
Humans are capable of adjusting to changing environments flexibly and qu...
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01/13/2022
Non-Stationary Representation Learning in Sequential Linear Bandits
In this paper, we study representation learning for multi-task decision-...
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04/06/2021
Taming Adversarial Robustness via Abstaining
In this work, we consider a binary classification problem and cast it in...
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03/30/2021
Learning Robust Feedback Policies from Demonstrations
In this work we propose and analyze a new framework to learn feedback co...
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06/25/2020
Habit learning supported by efficiently controlled network dynamics in naive macaque monkeys
Primates display a marked ability to learn habits in uncertain and dynam...
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06/18/2020
Learning Minimum-Energy Controls from Heterogeneous Data
In this paper we study the problem of learning minimum-energy controls f...
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06/05/2020
Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing
In this work we propose a graph-based learning framework to train models...
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03/17/2020
Data-Driven Attack Detection for Linear Systems
This paper studies the attack detection problem in a data-driven and mod...
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02/18/2020
Network Theoretic Analysis of Maximum a Posteriori Detectors for Sensor Analysis and Design
In this paper we characterize the performance of a class of maximum-a-po...
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12/21/2019
On the Robustness of Data-Driven Controllers for Linear Systems
This paper proposes a new framework and several results to quantify the ...
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03/04/2019