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2020 – today
- 2023
[j2]Si-An Chen, Chun-Liang Li, Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister:
TSMixer: An All-MLP Architecture for Time Series Forecast-ing. Trans. Mach. Learn. Res. 2023 (2023)- [c4]Yu-Chen Lin, Si-An Chen, Jie-Jyun Liu, Chih-Jen Lin:
Linear Classifier: An Often-Forgotten Baseline for Text Classification. ACL (2) 2023: 1876-1888 - [i9]Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan Ö. Arik, Tomas Pfister:
TSMixer: An all-MLP Architecture for Time Series Forecasting. CoRR abs/2303.06053 (2023) - [i8]Yu-Chen Lin, Si-An Chen, Jie-Jyun Liu, Chih-Jen Lin:
Linear Classifier: An Often-Forgotten Baseline for Text Classification. CoRR abs/2306.07111 (2023) - [i7]Paul Kuo-Ming Huang, Si-An Chen, Hsuan-Tien Lin:
Score-based Conditional Generation with Fewer Labeled Data by Self-calibrating Classifier Guidance. CoRR abs/2307.04081 (2023) - [i6]Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister:
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models. CoRR abs/2308.00675 (2023) - 2022
- [c3]Si-An Chen, Jie-Jyun Liu, Tsung-Han Yang, Hsuan-Tien Lin, Chih-Jen Lin:
Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN. NAACL-HLT 2022: 1987-2000 - 2021
- [c2]Jie-Jyun Liu, Tsung-Han Yang, Si-An Chen, Chih-Jen Lin:
Parameter Selection: Why We Should Pay More Attention to It. ACL/IJCNLP (2) 2021: 825-830 - [c1]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
A Unified View of cGANs with and without Classifiers. NeurIPS 2021: 27566-27579 - [i5]Jie-Jyun Liu, Tsung-Han Yang, Si-An Chen, Chih-Jen Lin:
Parameter Selection: Why We Should Pay More Attention to It. CoRR abs/2107.05393 (2021) - [i4]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
A Unified View of cGANs with and without Classifiers. CoRR abs/2111.01035 (2021) - [i3]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration. CoRR abs/2111.02316 (2021) - 2020
- [j1]Si-An Chen
, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama:
Active deep Q-learning with demonstration. Mach. Learn. 109(9-10): 1699-1725 (2020)
2010 – 2019
- 2018
- [i2]Si-An Chen, Voot Tangkaratt, Hsuan-Tien Lin, Masashi Sugiyama:
Active Deep Q-learning with Demonstration. CoRR abs/1812.02632 (2018) - 2017
- [i1]Yao-Yuan Yang, Shao-Chuan Lee, Yu-An Chung, Tung-En Wu, Si-An Chen, Hsuan-Tien Lin:
libact: Pool-based Active Learning in Python. CoRR abs/1710.00379 (2017)
Coauthor Index
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