I am currently a Machine Learning Researcher at the Cortex Applied Research team at Twitter, with a focus on recommender system and reinforcement learning. Prior to Twitter, I obtained my PhD from Statistics and Data Science Department in University of Texas at Austin, supervised by Dr.Mingyuan Zhou. My research interest is Bayesian statistics, with applications including Reinforcement Learning and Generative Models. I am also interested in optimization.

In my spare time, I like playing tennis and piano.

Education

• Ph.D in University of Texas at Austin, 2021
• M.S. in University of California, Los Angeles, 2017
• B.S. in Fudan University, 2015

Publications

Clinical Implications of the T790M Mutation in Disease Characteristics and Treatment Response in Patients With Epidermal Growth Factor Receptor (EGFR)-Mutated Non–Small-Cell Lung Cancer (NSCLC)

D. Gaut, M. Sim, Y. Yue, B. Wolf, P. Abarca, J. Carroll, J. Goldman, E. Garon. "Clinical Implications of the T790M Mutation in Disease Characteristics and Treatment Response in Patients With Epidermal Growth Factor Receptor (EGFR)-Mutated Non–Small-Cell Lung Cancer (NSCLC)" Clinical Lung Cancer(2018).

T-optimal designs for multi-factor polynomial regression models via a semidefinite relaxation method

Y. Yue, L. Vandenberghe, W.K. Wong. "T-optimal designs for multi-factor polynomial regression models via a semidefinite relaxation method" Statistics and Computing(2018).

ARSM: Augment-REINFORCE-swap-merge estimator for gradient backpropagation through categorical variables

M. Yin*, Y. Yue*, M. Zhou . "ARSM: Augment-REINFORCE-swap-merge estimator for gradient backpropagation through categorical variables" ICML(2019).

Semi-supervised Learning using Adversarial Training with Good and Bad Samples

W. Li, Z. Wang, Y. Yue, J. Li, W. Speier, M. Zhou, C. Arnold. "Semi-supervised Learning using Adversarial Training with Good and Bad Samples" Machine Vision and Applications(2020).

Discrete action on-policy learning with action-value critic

Y. Yue, Y. Tang, M. Yin, and M. Zhou . "Discrete action on-policy learning with action-value critic" AISTATS(2020).

A Unified Framework for Tuning Hyperparameters in Clustering Problems

X. Fan, Y. Yue, P. Sarkar, R. Wang . "A Unified Framework for Tuning Hyperparameters in Clustering Problems" ICML(2020).

Implicit Distributional Reinforcement Learning

Y. Yue*, Z. Wang*, and M. Zhou . "Implicit Distributional Reinforcement Learning" Neurips(2020).

Learning to Rank For Push Notifications Using Pairwise Expected Regret

Y. Yue*, Y. Xie, H. Wu, H. Jia, S. Zhai, W. Shi, J. Hunt*. "Learning to Rank For Push Notifications Using Pairwise Expected Regret" Arxiv(2022).

Work experience

• Twitter: Machine Learning Researcher (From June 2021)
  • Work on building recommender for the new explore page
  • Improve Ads ranking model with multitask learning techniques
  • Build simulation systems with JAX
• Nuro: Machine Learning Researcher Intern (Spring 2021)
  • Improve the agent using imitation learning technique
• Twitter: Machine Learning Research Engineer Intern (Summer, Fall 2020)
  • Improve push notification recommendation system
• Bytedance: Research Intern (Winter 2019)
  • Build Bayesian testing platform
  • Tune hyperparameter with Bayesian Optimization
• Twitter: Data Scientist Intern (Summer 2019)
  • Metric clustering
• Twitter: Data Scientist Intern (Summer 2018)
  • CUPED extension
• VMWare: R&D Intern (Summer 2017)
  • Develop bug auto-triage tool