activity
20162024
most citedTowards a Science of Human-AI Decision Making: A Survey of Empirical Studies

76 citations · 102 across the 11 of their papers we have counts for

collaborators

11 papers

cs.HC2024

OpenHEXAI: An Open-Source Framework for Human-Centered Evaluation of Explainable Machine Learning

Jiaqi Ma, Vivian Lai, Yiming Zhang +5

Recently, there has been a surge of explainable AI (XAI) methods driven by the need for understanding machine learning model behaviors in high-stakes scenarios. However, properly e…

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.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.IR2023

An Efficient Content-based Time Series Retrieval System

Chin-Chia Michael Yeh, Huiyuan Chen, Xin Dai +9

A Content-based Time Series Retrieval (CTSR) system is an information retrieval system for users to interact with time series emerged from multiple domains, such as finance, health…

cs.LG2023

Toward a Foundation Model for Time Series Data

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

A foundation model is a machine learning model trained on a large and diverse set of data, typically using self-supervised learning-based pre-training techniques, that can be adapt…