Research Interests

  • Statistical Machine Learning

  • Feedback-Driven Machine Learning

  • Sequential Decision Making

  • Deep Learning

  • Natural Language Processing

Publications & Preprints

Asterisks (*) denote equal contribution.

  • Comparing Sequential Forecasters (arxiv, code)
    Y. Choe, A. Ramdas
    Preprint (2021)
    Preliminary work presented at JSM 2021.

  • An Empirical Study of Invariant Risk Minimization (arxiv, code)
    Y. Choe, J. Ham, K. Park
    ICML Workshop on Uncertainty and Robustness in Deep Learning (2020)

  • KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding (paper, arxiv, data)
    J. Ham*, Y. Choe*, K. Park*, I. Choi, H. Soh
    Findings of the Association for Computational Linguistics: EMNLP (2020)

  • word2word: A Collection of Bilingual Lexicons for 3,564 Language Pairs (paper, arxiv, code)
    Y. Choe*, K. Park*, D. Kim*
    Proceedings of the 12th Language Resources and Evaluation Conference (2020)

  • Jejueo Datasets for Machine Translation and Speech Synthesis (paper, arxiv, code)
    K. Park, Y. Choe, J. Ham
    Proceedings of the 12th Language Resources and Evaluation Conference (2020)

  • Predicting Drug–Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation (paper, arxiv)
    J. Lim, S. Ryu, K. Park, Y. Choe, J. Ham, W. Kim
    Journal of Chemical Information and Modeling (2019)

  • A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer Learning (paper, arxiv, code)
    Y. Choe*, J. Ham*, K. Park*, Y. Yoon*
    Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications (2019)
    Second Place in the GEC Shared Task (Restricted & Low Resource Tracks)

  • Discovery of Natural Language Concepts in Individual Units of CNNs (paper, arxiv, poster, code)
    S. Na, Y. Choe, D. Lee, G. Kim
    International Conference on Learning Representations (2019)

  • Local White Matter Architecture Defines Functional Brain Dynamics (paper, arxiv, slides)
    Y. Choe, S. Balakrishnan, A. Singh, J. Vettel, T. Verstynen
    IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2018)
    Franklin V. Taylor Memorial Best Paper Award

  • Learning Diverse Overcomplete Dictionaries via Determinantal Priors (abstract)
    M. Al-Shedivat, Y. Choe, N. Spencer, E. Xing
    ICML Workshop on Geometry in Machine Learning (2016)


  • Probabilistic Interpretations of Recurrent Neural Networks (report)
    Collaborators: J. Shin, N. Spencer
    CMU Course Project (2017)

  • A Statistical Analysis of Neural Networks (report)
    CMU Course Project (2016)

  • Deep Learning for Socioeconomic Inference Using Google Street View Images (blog)
    Mentors/Collaborators: J. Evans, N. Sauder, Z. Dai, R. Turner, V. Vora
    University of Chicago Knowledge Lab (2014–2015)

  • Sparse Additive Models with Shape Constraints (report, slides, code)
    Mentors: J. Lafferty, S. Chatterjee, M. Xu
    University of Chicago Computer Science REU (2014)