12 citations · 24 across the 3 of their papers we have counts for
8 papers
Smooth Bandit Optimization: Generalization to Hölder Space
Yusha Liu, Yining Wang, Aarti Singh
We consider bandit optimization of a smooth reward function, where the goal is cumulative regret minimization. This problem has been studied for -Hölder continuous (including Li…
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…
Robust Nonparametric Regression under Huber's -contamination Model
Simon S. Du, Yining Wang, Sivaraman Balakrishnan +2
We consider the non-parametric regression problem under Huber's -contamination model, in which an fraction of observations are subject to arbitrary adversarial noise. We fir…
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…