6 citations · 17 across the 9 of their papers we have counts for
6 papers · 1 filter
Adaptive Partitioning Schemes for Optimistic Optimization
Raja Sunkara, Ardhendu Tripathy
Applications such as engineering design often require us to optimize a black-box function, i.e., a system whose inner processing is not analytically known and whose gradients are n…
Nearest Neighbor Search Under Uncertainty
Blake Mason, Ardhendu Tripathy, Robert Nowak
Nearest Neighbor Search (NNS) is a central task in knowledge representation, learning, and reasoning. There is vast literature on efficient algorithms for constructing data structu…
Chernoff Sampling for Active Testing and Extension to Active Regression
Subhojyoti Mukherjee, Ardhendu Tripathy, Robert Nowak
Active learning can reduce the number of samples needed to perform a hypothesis test and to estimate the parameters of a model. In this paper, we revisit the work of Chernoff that…
Optimal Confidence Regions for the Multinomial Parameter
Matthew L. Malloy, Ardhendu Tripathy, Robert D. Nowak
Construction of tight confidence regions and intervals is central to statistical inference and decision making. This paper develops new theory showing minimum average volume confid…
MaxGap Bandit: Adaptive Algorithms for Approximate Ranking
Sumeet Katariya, Ardhendu Tripathy, Robert Nowak
This paper studies the problem of adaptively sampling from K distributions (arms) in order to identify the largest gap between any two adjacent means. We call this the MaxGap-bandi…
Learning Nearest Neighbor Graphs from Noisy Distance Samples
Blake Mason, Ardhendu Tripathy, Robert Nowak
We consider the problem of learning the nearest neighbor graph of a dataset of n items. The metric is unknown, but we can query an oracle to obtain a noisy estimate of the distance…