49 citations · 53 across the 6 of their papers we have counts for
7 papers
Enhancing Text-Based Hierarchical Multilabel Classification for Mobile Applications via Contrastive Learning
Jiawei Guo, Yang Xiao, Weipeng Huang +1
A hierarchical labeling system for mobile applications (apps) benefits a wide range of downstream businesses that integrate the labeling with their proprietary user data, to improv…
Correcting Noisy Multilabel Predictions: Modeling Label Noise through Latent Space Shifts
Weipeng Huang, Qin Li, Yang Xiao +5
Noise in data appears to be inevitable in most real-world machine learning applications and would cause severe overfitting problems. Not only can data features contain noise, but l…
Rényi Divergence Deep Mutual Learning
Weipeng Huang, Junjie Tao, Changbo Deng +4
This paper revisits Deep Mutual Learning (DML), a simple yet effective computing paradigm. We propose using Rényi divergence instead of the KL divergence, which is more flexible an…
Partially Observable Markov Decision Process Modelling for Assessing Hierarchies
Weipeng Huang, Guangyuan Piao, Raul Moreno +1
Hierarchical clustering has been shown to be valuable in many scenarios. Despite its usefulness to many situations, there is no agreed methodology on how to properly evaluate the h…
Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach
Weipeng Huang, Nishma Laitonjam, Guangyuan Piao +1
This paper focuses on the problem of hierarchical non-overlapping clustering of a dataset. In such a clustering, each data item is associated with exactly one leaf node and each in…
Inferring User Interests in Microblogging Social Networks: A Survey
Guangyuan Piao, John G. Breslin
With the growing popularity of microblogging services such as Twitter in recent years, an increasing number of users are using these services in their daily lives. The huge volume…
Factorization Machines Leveraging Lightweight Linked Open Data-enabled Features for Top-N Recommendations
Guangyuan Piao, John G. Breslin
With the popularity of Linked Open Data (LOD) and the associated rise in freely accessible knowledge that can be accessed via LOD, exploiting LOD for recommender systems has been w…