6 citations · 14 across the 5 of their papers we have counts for
9 papers
Uncertainty-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric
Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar +1
In this paper, we consider the problem of using a robot to explore an environment with an unknown, state-dependent disturbance function while avoiding some forbidden areas. The goa…
Adaptive Sampling for Minimax Fair Classification
Shubhanshu Shekhar, Greg Fields, Mohammad Ghavamzadeh +1
Machine learning models trained on uncurated datasets can often end up adversely affecting inputs belonging to underrepresented groups. To address this issue, we consider the probl…
Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS
Shubhanshu Shekhar, Tara Javidi
We aim to optimize a black-box function under the assumption that is Hölder smooth and has bounded norm in the RKHS associated with a given k…
Active Model Estimation in Markov Decision Processes
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta +2
We study the problem of efficient exploration in order to learn an accurate model of an environment, modeled as a Markov decision process (MDP). Efficient exploration in this probl…
Adaptive Sampling for Estimating Multiple Probability Distributions
Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh
We consider the problem of allocating samples to a finite set of discrete distributions in order to learn them uniformly well in terms of four common distance measures: ,…
Active Learning for Binary Classification with Abstention
Shubhanshu Shekhar, Mohammad Ghavamzadeh, Tara Javidi
We construct and analyze active learning algorithms for the problem of binary classification with abstention. We consider three abstention settings: \emph{fixed-cost} and two varia…