Machine Learning

Overview

The USC Melady Lab develops machine learning and data mining algorithms for solving problems involving data with special structure, including time series, spatiotemporal data, and relational data. We work closely with domain experts to solve challenging problems and make significant impacts in computational biology, social media analysis, climate modeling, health care, and business intelligence.

Selected Publications in Transportation

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Yaguang Li, Rose Yu, Cyrus Shahabi and Yan Liu
arXiv preprint arXiv:1707.01926

Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting
Yaguang Li*, Rose Yu*, Cyrus Shahabi, Ugur Demiryurek and Yan Liu (*Equal Contribution)
Proceedings of the 2017 SIAM International Conference on Data Mining (SDM), 2017.

Latent Space Model for Road Networks to Predict Time-Varying Traffic
Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, Yan Liu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016.

Selected Publications in Health

Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records
Zhengping Che*, Yu Cheng*, Shuangfei Zhai, Zhaonan Sun, and Yan Liu. (*contributed equally)
To appear in the IEEE 17th International Conference on Data Mining (ICDM), 2017.

Deep Learning Solutions for Classifying Patients on Opioid Use
Zhengping Che, Jennifer St. Sauver, Hongfang Liu, and Yan Liu.
To appear in the American Medical Informatics Assocation Annual Symposium (AMIA), 2017.

Interpretable Deep Models for ICU Outcome Prediction
Zhengping Che, Sanjay Purushotham, Robinder Khemani, and Yan Liu.
Proceedings of the American Medical Informatics Assocation Annual Symposium (AMIA), 2016.

Deep Computational Phenotyping
Zhengping Che*, David C. Kale*, Wenzhe Li, Mohammad Taha Bahadori, and Yan Liu. (*contributed equally)
Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2015.

An Examination of Multivariate Time Series Hashing with Applications to Health Care
David C. Kale*, Dian Gong*, Zhengping Che*, Gerard Medioni, Randall Wetzel, Patrick Ross, and Yan Liu. (*contributed equally)
Proceedings of the IEEE 14th International Conference on Data Mining (ICDM), 2014.

Yan Liu

Associate Professor of Computer Science Dept.
Director, USC Machine Learning Center
USC

USC Melady Lab

The USC Melady Lab develops machine learning and data mining algorithms for solving problems involving data with special structure, including time series, spatiotemporal data, and relational data.

USC Melady Lab

IMSC is a research center that focuses on data-driven solutions for real-world applications by applying multidisciplinary research in the area of data science.