activity
20222024
most citedTowards Mitigating Dimensional Collapse of Representations in Collaborative Filtering

15 citations · 32 across the 16 of their papers we have counts for

collaborators

16 papers

cs.IR2024

Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness

Yuying Zhao, Minghua Xu, Huiyuan Chen +5

Recommender systems (RSs) have gained widespread applications across various domains owing to the superior ability to capture users' interests. However, the complexity and nuanced…

cs.IR202315 cited

Towards Mitigating Dimensional Collapse of Representations in Collaborative Filtering

Huiyuan Chen, Vivian Lai, Hongye Jin +3

Contrastive Learning (CL) has shown promising performance in collaborative filtering. The key idea is to generate augmentation-invariant embeddings by maximizing the Mutual Informa…

cs.DB2023

Time Series Synthesis Using the Matrix Profile for Anonymization

Audrey Der, Chin-Chia Michael Yeh, Yan Zheng +6

Publishing and sharing data is crucial for the data mining community, allowing collaboration and driving open innovation. However, many researchers cannot release their data due to…

cs.LG2023

Ego-Network Transformer for Subsequence Classification in Time Series Data

Chin-Chia Michael Yeh, Huiyuan Chen, Yujie Fan +8

Time series classification is a widely studied problem in the field of time series data mining. Previous research has predominantly focused on scenarios where relevant or foregroun…

cs.IR2023

Temporal Treasure Hunt: Content-based Time Series Retrieval System for Discovering Insights

Chin-Chia Michael Yeh, Huiyuan Chen, Xin Dai +8

Time series data is ubiquitous across various domains such as finance, healthcare, and manufacturing, but their properties can vary significantly depending on the domain they origi…

cs.LG2023

Multitask Learning for Time Series Data with 2D Convolution

Chin-Chia Michael Yeh, Xin Dai, Yan Zheng +7

Multitask learning (MTL) aims to develop a unified model that can handle a set of closely related tasks simultaneously. By optimizing the model across multiple tasks, MTL generally…