41 citations · 87 across the 8 of their papers we have counts for
8 papers
Active Sequential Two-Sample Testing
Weizhi Li, Prad Kadambi, Pouria Saidi +3
A two-sample hypothesis test is a statistical procedure used to determine whether the distributions generating two samples are identical. We consider the two-sample testing problem…
A label-efficient two-sample test
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy +1
Two-sample tests evaluate whether two samples are realizations of the same distribution (the null hypothesis) or two different distributions (the alternative hypothesis). We consid…
Finding the Homology of Decision Boundaries with Active Learning
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy +1
Accurately and efficiently characterizing the decision boundary of classifiers is important for problems related to model selection and meta-learning. Inspired by topological data…
Regularization via Structural Label Smoothing
Weizhi Li, Gautam Dasarathy, Visar Berisha
Regularization is an effective way to promote the generalization performance of machine learning models. In this paper, we focus on label smoothing, a form of output distribution r…
Time-weighted Attentional Session-Aware Recommender System
Mei Wang, Weizhi Li, Yan Yan
Session-based Recurrent Neural Networks (RNNs) are gaining increasing popularity for recommendation task, due to the high autocorrelation of user's behavior on the latest session a…
A novel image tag completion method based on convolutional neural network
Yanyan Geng, Guohui Zhang, Weizhi Li +7
In the problems of image retrieval and annotation, complete textual tag lists of images play critical roles. However, in real-world applications, the image tags are usually incompl…
Learning convolutional neural network to maximize Pos@Top performance measure
Yanyan Geng, Ru-Ze Liang, Weizhi Li +4
In the machine learning problems, the performance measure is used to evaluate the machine learning models. Recently, the number positive data points ranked at the top positions (Po…
A novel transfer learning method based on common space mapping and weighted domain matching
Ru-Ze Liang, Wei Xie, Weizhi Li +3
In this paper, we propose a novel learning framework for the problem of domain transfer learning. We map the data of two domains to one single common space, and learn a classifier…