Yuda Song

Hi, I am a first-year master student at Machine Learning Department, Carnegie Mellon University . I am currently advised by Kris Kitani and working with Wen Sun. I completed my undergraduate at UCSD with CS and Math double major and I am very fortunate to be advised by Sicun Gao at UCSD.

Email  /  CV  /  Github

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Research

I am broadly interested in machine learning, especially reinforcement learning. I am interested in developing algorithms with theoretical guarantees and also testing their empirical counterparts in practice. My current focus is on model-based RL, imitation learning and exploration in RL.

Publication
PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration
Yuda Song, Wen Sun
ICML, 2021

[code]
Provably Efficient Model-based Policy Adaptation
Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao
ICML, 2020

[Project Page] [code]
Teaching Assistant

  • UCSD CSE291: Topics in Search and Optimization (Winter 2020)
  • UCSD CSE154: Deep Learning (Fall 2019)
  • UCSD CSE150: Introduction to AI: Search and Reasoning (Winter 2019, Spring 2020)
  • UCSD CSE30: Computer Organization and Systems Programming (Spring 2019, Winter 2018)
  • UCSD CSE11: Introduction to CS & OOP (Fall 2018)

  • Service

  • Reviewer: AAAI (2021), ICML (2021), NeurIPS (2021).


  • Source code from here