no code implementations • LTEDI (ACL) 2022 • Wei-Yao Wang, Yu-Chien Tang, Wei-Wei Du, Wen-Chih Peng
This paper presents a state-of-the-art solution to the LT-EDI-ACL 2022 Task 4: Detecting Signs of Depression from Social Media Text.
1 code implementation • 14 Dec 2024 • Hong-Wei Wu, Wei-Yao Wang, Kuang-Da Wang, Wen-Chih Peng
Tabular data are fundamental in common machine learning applications, ranging from finance to genomics and healthcare.
no code implementations • 16 Oct 2024 • Ching Chang, Chiao-Tung Chan, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen
Multivariate time-series data in fields like healthcare and industry are informative but challenging due to high dimensionality and lack of labels.
1 code implementation • 19 Mar 2024 • Kuang-Da Wang, Wei-Yao Wang, Ping-Chun Hsieh, Wen-Chih Peng
(iii) To generate more realistic behavior, RallyNet leverages Geometric Brownian Motion (GBM) to model the interactions between players by introducing a valuable inductive bias for learning player behaviors.
1 code implementation • 2 Feb 2024 • Wei-Yao Wang, Wei-Wei Du, Derek Xu, Wei Wang, Wen-Chih Peng
Recently, SSL has become a new trend in exploring the representation learning capability in the realm of tabular data, which is more challenging due to not having explicit relations for learning descriptive representations.
1 code implementation • 2 Feb 2024 • Cheng-Ming Lin, Ching Chang, Wei-Yao Wang, Kuang-Da Wang, Wen-Chih Peng
To address these challenges, we propose RUN, a novel approach for root cause analysis using neural Granger causal discovery with contrastive learning.
no code implementations • 27 Jan 2024 • Wei-Yao Wang, Yu-Chieh Chang, Wen-Chih Peng
In this paper, we focus on neural fake news, which refers to content generated by neural networks aiming to mimic the style of real news to deceive people.
1 code implementation • 18 Dec 2023 • Wei-Yao Wang, Wen-Chih Peng, Wei Wang, Philip S. Yu
Agent forecasting systems have been explored to investigate agent patterns and improve decision-making in various domains, e. g., pedestrian predictions and marketing bidding.
1 code implementation • 17 Dec 2023 • Ying-Ying Chang, Wei-Yao Wang, Wen-Chih Peng
In the dynamic and rapidly evolving world of social media, detecting anomalous users has become a crucial task to address malicious activities such as misinformation and cyberbullying.
1 code implementation • 7 Dec 2023 • Ching Chang, Chiao-Tung Chan, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen
Multivariate time-series data in numerous real-world applications (e. g., healthcare and industry) are informative but challenging due to the lack of labels and high dimensionality.
1 code implementation • 15 Oct 2023 • Yu-Chien Tang, Wei-Yao Wang, An-Zi Yen, Wen-Chih Peng
Existing intent detection approaches have highly relied on adaptively pre-training language models with large-scale datasets, yet the predominant cost of data collection may hinder their superiority.
1 code implementation • 2 Sep 2023 • Wei-Wei Du, Wei-Yao Wang, Wen-Chih Peng
Existing automated valuation models reducing the subjectivity of domain experts require a large number of transactions for effective evaluation, which is predominantly limited to not only the labeling efforts of transactions but also the generalizability of new developing and rural areas.
no code implementations • 16 Aug 2023 • Ching Chang, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen
Recently, researchers have leveraged the representation learning transferability of pre-trained Large Language Models (LLMs) to handle limited non-linguistic datasets effectively.
1 code implementation • 27 Jun 2023 • Wei-Yao Wang, Wei-Wei Du, Wen-Chih Peng, Tsi-Ui Ik
In recent years, badminton analytics has drawn attention due to the advancement of artificial intelligence and the efficiency of data collection.
2 code implementations • 8 Jun 2023 • Wei-Yao Wang, Yung-Chang Huang, Tsi-Ui Ik, Wen-Chih Peng
With the recent progress in sports analytics, deep learning approaches have demonstrated the effectiveness of mining insights into players' tactics for improving performance quality and fan engagement.
1 code implementation • 7 Jun 2023 • Xiusi Chen, Wei-Yao Wang, Ziniu Hu, David Reynoso, Kun Jin, Mingyan Liu, P. Jeffrey Brantingham, Wei Wang
In this study, we formulate the sequential decision-making process as a conditional trajectory generation process.
1 code implementation • 12 Feb 2023 • Wei-Wei Du, Hong-Wei Wu, Wei-Yao Wang, Wen-Chih Peng
Multi-modal fact verification has become an important but challenging issue on social media due to the mismatch between the text and images in the misinformation of news content, which has been addressed by considering cross-modalities to identify the veracity of the news in recent years.
no code implementations • 23 Dec 2022 • Chih-Chia Li, Wei-Yao Wang, Wei-Wei Du, Wen-Chih Peng
However, existing methods only consider the real estate itself, ignoring the relation between the properties.
1 code implementation • 22 Nov 2022 • Kai-Shiang Chang, Wei-Yao Wang, Wen-Chih Peng
To address these challenges, we first introduce the procedure of the Player Movements (PM) graph to exploit the structural movements of players with strategic relations.
1 code implementation • 22 Nov 2022 • Li-Chun Huang, Nai-Zen Hseuh, Yen-Che Chien, Wei-Yao Wang, Kuang-Da Wang, Wen-Chih Peng
Recent techniques for analyzing sports precisely has stimulated various approaches to improve player performance and fan engagement.
2 code implementations • 29 Oct 2022 • Wei-Wei Du, Wei-Yao Wang, Wen-Chih Peng
Recommendation systems have illustrated the significant progress made in characterizing users' preferences based on their past behaviors.
1 code implementation • 26 Jan 2022 • Wei-Yao Wang, Wen-Chih Peng
In recent years, social media has enabled users to get exposed to a myriad of misinformation and disinformation; thus, misinformation has attracted a great deal of attention in research fields and as a social issue.
1 code implementation • 2 Dec 2021 • Wei-Yao Wang, Hong-Han Shuai, Kai-Shiang Chang, Wen-Chih Peng
The increasing demand for analyzing the insights in sports has stimulated a line of productive studies from a variety of perspectives, e. g., health state monitoring, outcome prediction.
2 code implementations • 14 Sep 2021 • Wei-Yao Wang, Teng-Fong Chan, Hui-Kuo Yang, Chih-Chuan Wang, Yao-Chung Fan, Wen-Chih Peng
In this paper, we introduce a badminton language to fully describe the process of the shot and propose a deep learning model composed of a novel short-term extractor and a long-term encoder for capturing a shot-by-shot sequence in a badminton rally by framing the problem as predicting a rally result.
1 code implementation • 5 Jul 2020 • Wei-Yao Wang, Kai-Shiang Chang, Yu-Chien Tang
This paper provides a method to classify sentiment with robust model based ensemble methods.
3 code implementations • CVPR 2020 • Wei-Yao Wang, Du Tran, Matt Feiszli
Consider end-to-end training of a multi-modal vs. a single-modal network on a task with multiple input modalities: the multi-modal network receives more information, so it should match or outperform its single-modal counterpart.
Ranked #1 on
Action Recognition In Videos
on miniSports
no code implementations • 1 May 2019 • Rong Ge, Zhize Li, Wei-Yao Wang, Xiang Wang
Variance reduction techniques like SVRG provide simple and fast algorithms for optimizing a convex finite-sum objective.
no code implementations • 24 Apr 2019 • Xinlei Pan, Wei-Yao Wang, Xiaoshuai Zhang, Bo Li, Jin-Feng Yi, Dawn Song
To the best of our knowledge, this is the first work to investigate privacy leakage in DRL settings and we show that DRL-based agents do potentially leak privacy-sensitive information from the trained policies.
2 code implementations • ICML 2018 • Yunchen Pu, Shuyang Dai, Zhe Gan, Wei-Yao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin
Distinct from most existing approaches, that only learn conditional distributions, the proposed model aims to learn a joint distribution of multiple random variables (domains).
no code implementations • NeurIPS 2017 • Yunchen Pu, Wei-Yao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin
A new form of variational autoencoder (VAE) is developed, in which the joint distribution of data and codes is considered in two (symmetric) forms: ($i$) from observed data fed through the encoder to yield codes, and ($ii$) from latent codes drawn from a simple prior and propagated through the decoder to manifest data.
1 code implementation • NeurIPS 2017 • Zhe Gan, Liqun Chen, Wei-Yao Wang, Yunchen Pu, Yizhe Zhang, Hao liu, Chunyuan Li, Lawrence Carin
The generators are designed to learn the two-way conditional distributions between the two domains, while the discriminators implicitly define a ternary discriminative function, which is trained to distinguish real data pairs and two kinds of fake data pairs.