research
∙
11/23/2022
Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations
Deep Candidate Generation plays an important role in large-scale recomme...
share
research
∙
10/14/2021
Escaping Saddle Points in Nonconvex Minimax Optimization via Cubic-Regularized Gradient Descent-Ascent
The gradient descent-ascent (GDA) algorithm has been widely applied to s...
research
∙
12/07/2020
Learning Graph Neural Networks with Approximate Gradient Descent
The first provably efficient algorithm for learning graph neural network...
research
∙
09/03/2019
Prospect Theory Based Crowdsourcing for Classification in the Presence of Spammers
We consider the M-ary classification problem via crowdsourcing, where cr...
research
∙
06/06/2019
A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis
This paper provides a general framework to study the effect of sampling ...
research
∙
11/22/2018
MR-GAN: Manifold Regularized Generative Adversarial Networks
Despite the growing interest in generative adversarial networks (GANs), ...
research
∙
07/31/2018
K-medoids Clustering of Data Sequences with Composite Distributions
This paper studies clustering of data sequences using the k-medoids algo...
research
∙
05/01/2018
Decision Tree Design for Classification in Crowdsourcing Systems
In this paper, we present a novel sequential paradigm for classification...
research
∙
12/08/2017
Nonparametric Composite Hypothesis Testing in an Asymptotic Regime
We investigate the nonparametric, composite hypothesis testing problem f...
research
∙
10/26/2017
Optimal Crowdsourced Classification with a Reject Option in the Presence of Spammers
We explore the design of an effective crowdsourcing system for an M-ary ...
research
∙
10/14/2017