Feature Ranking Using Linear SVM. - Yin-Wen Chang; Chih-Jen Lin (WCCI Causation and Prediction Challenge, 2008)

Training and Testing Low-degree Polynomial Data Mappings via Linear SVM. - Yin-Wen Chang; Cho-Jui Hsieh; Kai-Wei Chang; Michael Ringgaard; Chih-Jen Lin (J. Mach. Learn. Res., 2010)

Exact Decoding of Phrase-Based Translation Models through Lagrangian Relaxation. - Yin-Wen Chang; Michael Collins 001 (EMNLP, 2011)

Optimal Beam Search for Machine Translation. - Alexander M. Rush; Yin-Wen Chang; Michael Collins 001 (EMNLP, 2013)

A Constrained Viterbi Relaxation for Bidirectional Word Alignment. - Yin-Wen Chang; Alexander M. Rush; John DeNero; Michael Collins 001 (ACL (1), 2014)

Exact and Approximate Methods for Machine Translation Decoding. - Yin-Wen Chang (2015)

Source-Side Left-to-Right or Target-Side Left-to-Right? An Empirical Comparison of Two Phrase-Based Decoding Algorithms. - Yin-Wen Chang; Michael Collins 001 (EMNLP, 2017)

A Polynomial-Time Dynamic Programming Algorithm for Phrase-Based Decoding with a Fixed Distortion Limit. - Yin-Wen Chang; Michael Collins 001 (Trans. Assoc. Comput. Linguistics, 2017)

Pre-training Tasks for Embedding-based Large-scale Retrieval. - Wei-Cheng Chang; Felix X. Yu; Yin-Wen Chang; Yiming Yang; Sanjiv Kumar (ICLR, 2020)

O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers. - Chulhee Yun; Yin-Wen Chang; Srinadh Bhojanapalli; Ankit Singh Rawat; Sashank J. Reddi; Sanjiv Kumar (NeurIPS, 2020)

A Simple and Effective Positional Encoding for Transformers. - Pu-Chin Chen; Henry Tsai; Srinadh Bhojanapalli; Hyung Won Chung; Yin-Wen Chang; Chun-Sung Ferng (EMNLP (1), 2021)

Demystifying the Better Performance of Position Encoding Variants for Transformer. - Pu-Chin Chen; Henry Tsai; Srinadh Bhojanapalli; Hyung Won Chung; Yin-Wen Chang; Chun-Sung Ferng (CoRR, 2021)

Leveraging redundancy in attention with Reuse Transformers. - Srinadh Bhojanapalli; Ayan Chakrabarti; Andreas Veit; Michal Lukasik; Himanshu Jain; Frederick Liu; Yin-Wen Chang; Sanjiv Kumar (CoRR, 2021)

Better autoregressive regression with LLMs via regression-aware fine-tuning. - Michal Lukasik; Zhao Meng; Harikrishna Narasimhan; Yin-Wen Chang; Aditya Krishna Menon; Felix Yu; Sanjiv Kumar (ICLR, 2025)