12 citations · 24 across the 3 of their papers we have counts for
6 papers · 1 filter
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions
Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah +1
A number of applications require two-sample testing on ranked preference data. For instance, in crowdsourcing, there is a long-standing question of whether pairwise comparison data…
Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty
Yining Wang, Erva Ulu, Aarti Singh +1
An important task in structural design is to quantify the structural performance of an object under the external forces it may experience during its use. The problem proves to be c…
How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network?
Simon S. Du, Yining Wang, Xiyu Zhai +3
It is widely believed that the practical success of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) owes to the fact that CNNs and RNNs use a more compact…
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates
Yining Wang, Sivaraman Balakrishnan, Aarti Singh
We consider the problem of global optimization of an unknown non-convex smooth function with zeroth-order feedback. In this setup, an algorithm is allowed to adaptively query the u…
Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach
Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh +1
The experimental design problem concerns the selection of k points from a potentially large design pool of p-dimensional vectors, so as to maximize the statistical efficiency regre…
Computationally Efficient Robust Estimation of Sparse Functionals
Simon S. Du, Sivaraman Balakrishnan, Aarti Singh
Many conventional statistical procedures are extremely sensitive to seemingly minor deviations from modeling assumptions. This problem is exacerbated in modern high-dimensional set…