Seanie Lee (이신의)

Seanie Lee (이신의)

PhD. Student at KAIST

I am a PhD student at Machine Learning and Artificial Intelligence (MLAI) lab in KAIST, working on meta-learning and machine learning. I am fortunate to be advised by Professor Sung Ju Hwang and Juho Lee. I also closely collaborate with Kenji Kawaguchi. Here is my cv.

🔥 News

  • 2023.01:  🎉🎉 Two papers accepted to ICLR 2023.
  • 2022.10:  ✈️ Google Travel Grant for NeurIPS 2022 from Google.
  • 2022.09:  🎉🎉 Two papers accepted to NeurIPS 2022.
  • 2022.05:  🎉🎉 One paper accepted to ICML 2022.

📝 Publications

  • Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation

    [paper]
    Jeff Willette* Seanie Lee*, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
    Arxiv 2023

  • Self-Distillation for Further Pre-training of Transformers

    [paper]
    Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi
    ICLR 2023

  • Self-Supervised Set Representation Learning for Unsupervised Meta-Learning

    [paper]
    Dong Bok Lee*, Seanie Lee*, Kenji Kawaguchi, Yunji Kim, Jihwan Bang, Jung-Woo Ha, Sung Ju Hwang (*: equal contribution)
    ICLR 2023

  • Set-based Meta-Interpolation for Few-Task Meta-Learning

    [paper]
    Seanie Lee*, Bruno Andreis*, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang (*: equal contribution)
    NeurIPS 2022

  • On Divergence Measures for Bayesian Pseudocoresets

    [paper]
    Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha, Juho Lee
    NeurIPS 2022

  • Set Based Stochastic Subsampling

    [paper]
    Bruno Andreis, Seanie Lee, A. Tuan Nguyen, Juho Lee, Eunho Yang, Sung Ju Hwang
    ICML 2022

  • Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning

    [paper]
    Seanie Lee*, Hae Beom Lee*, Juho Lee, Sung Ju Hwang (*: equal contribution)
    ICLR 2022

  • Learning to Perturb Word Embeddings for Out-of-distribution QA

    [paper]
    Seanie Lee*, Minki Kang*, Juho Lee, Sung Ju Hwang (*: equal contribution)
    ACL 2021

  • Contrastive Learning with Adversarial Perturbations for Conditional Text Generation

    [paper]
    Seanie Lee*, Dong Bok Lee*, Sung Ju Hwang (*: equal contribution)
    ICLR 2021

  • Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning

    [paper]
    Dong Bok Lee, Dongchan Min, Seanie Lee, Sung Ju Hwang
    ICLR 2021

  • Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs

    [paper]
    Dong Bok Lee*, Seanie Lee*, WooTae Jeong, Donghwan Kim, Sung Ju Hwang (*: equal contribution)
    ACL 2020

  • g2pM: A Neural Grapheme-to-Phoneme Conversion Package for Mandarin Chinese Based on a New Open Benchmark Dataset

    [paper]
    Kyubyong Park*, Seanie Lee* (*: equal contribution)
    INTERSPEECH 2020

🎖 Honors and Awards

📖 Educations

  • 2022.03 - present, PhD. in Artificial Intelligence. Korea Advanced Institute of Science and Technology.
  • 2020.03 - 2022.02, M.S. in Artificial Intelligence. Korea Advanced Institute of Science and Technology.
  • 2011.03 - 2018.02, B.A. in Library and Information Science. Yonsei University.

💬 Invited Talks

  • 2021.12, Tech. talk, NAVER corp. Present ACL 2020 paper.

💻 Internships