58 citations · 205 across the 15 of their papers we have counts for
15 papers
Prospect Theory Based Crowdsourcing for Classification in the Presence of Spammers
Baocheng Geng, Qunwei Li, Pramod K. Varshney
We consider the -ary classification problem via crowdsourcing, where crowd workers respond to simple binary questions and the answers are aggregated via decision fusion. The wor…
A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis
Bhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li +1
This paper provides a general framework to study the effect of sampling properties of training data on the generalization error of the learned machine learning (ML) models. Specifi…
MR-GAN: Manifold Regularized Generative Adversarial Networks
Qunwei Li, Bhavya Kailkhura, Rushil Anirudh +3
Despite the growing interest in generative adversarial networks (GANs), training GANs remains a challenging problem, both from a theoretical and a practical standpoint. To address…
K-medoids Clustering of Data Sequences with Composite Distributions
Tiexing Wang, Qunwei Li, Donald J. Bucci +3
This paper studies clustering of data sequences using the k-medoids algorithm. All the data sequences are assumed to be generated from \emph{unknown} continuous distributions, whic…
Decision Tree Design for Classification in Crowdsourcing Systems
Baocheng Geng, Qunwei Li, Pramod K. Varshney
In this paper, we present a novel sequential paradigm for classification in crowdsourcing systems. Considering that workers are unreliable and they perform the tests with errors, w…
Nonparametric Composite Hypothesis Testing in an Asymptotic Regime
Qunwei Li, Tiexing Wang, Donald J. Bucci +3
We investigate the nonparametric, composite hypothesis testing problem for arbitrary unknown distributions in the asymptotic regime where both the sample size and the number of hyp…