Events Calendar

CS Colloquium: Yue Zhao (CMU) - Scalable and Automated Systems and Algorithms for Unsupervised ML

Speaker: Yue Zhao, Carnegie Mellon University

Talk Title: Scalable and Automated Systems and Algorithms for Unsupervised ML

Series: CS Colloquium

Abstract: Many real-world events do not have outcome labels. For example, the fraudulence of a transaction remains unknown until it is discovered. This is where unsupervised machine learning (ML) becomes crucial in real-world scenarios as it can make decisions based solely on observations. In this talk, I will address two key challenges in unsupervised ML: (i) developing scalable learning systems that can handle large amounts of data, and (ii) automating the selection of the best ML model. The first part of the talk will cover an ML system called TOD, which can "compile" a diverse group of ML algorithms for GPU acceleration. The second part will describe an automated algorithm called MetaOD, which can select top ML models for various applications without relying on labels or evaluations. Lastly, I will discuss my future plans, including the ML+X initiative, which aims to bring the advantages of ML systems and automation to other domains, and the creation of a fully automated ML pipeline that chooses hardware, systems, and models seamlessly.

This lecture satisfies requirements for CSCI 591: Research Colloquium

Biography: Yue Zhao is a Ph.D. candidate at CMU, working with Prof. Leman Akoglu and Prof. Zhihao Jia. He focuses on creating scalable and automated ML systems and algorithms, and has published over 30 papers in top venues such as VLDB, MLSys, JMLR, and NeurIPS. His open-source systems (https://github.com/yzhao062) have been widely deployed in firms and industries such as Morgan Stanley and Tesla, and have received over 15,000 GitHub stars and 10 million downloads. Yue has received the CMU Presidential Fellowship and Norton Graduate Fellowship. More information about him can be found at https://www.andrew.cmu.edu/user/yuezhao2/.

Host: Robin Jia

Location: Olin Hall of Engineering (OHE) - 132

Audiences: Everyone Is Invited

Contact: Assistant to CS chair