24 citations · 36 across the 10 of their papers we have counts for
5 papers
Lightweight, Uncertainty-Aware Conformalized Visual Odometry
Alex C. Stutts, Danilo Erricolo, Theja Tulabandhula +1
Data-driven visual odometry (VO) is a critical subroutine for autonomous edge robotics, and recent progress in the field has produced highly accurate point predictions in complex e…
Learning Personalized Optimal Control for Repeatedly Operated Systems
Theja Tulabandhula
We consider the problem of online learning of optimal control for repeatedly operated systems in the presence of parametric uncertainty. During each round of operation, environment…
Reinforcement Learning algorithms for regret minimization in structured Markov Decision Processes
K J Prabuchandran, Tejas Bodas, Theja Tulabandhula
A recent goal in the Reinforcement Learning (RL) framework is to choose a sequence of actions or a policy to maximize the reward collected or minimize the regret incurred in a fini…
Robust Optimization using Machine Learning for Uncertainty Sets
Theja Tulabandhula, Cynthia Rudin
Our goal is to build robust optimization problems for making decisions based on complex data from the past. In robust optimization (RO) generally, the goal is to create a policy fo…
Generalization Bounds for Learning with Linear, Polygonal, Quadratic and Conic Side Knowledge
Theja Tulabandhula, Cynthia Rudin
In this paper, we consider a supervised learning setting where side knowledge is provided about the labels of unlabeled examples. The side knowledge has the effect of reducing the…