ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning.
Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang
ICML 2017
About Me
I am a second year Ph.D student advised by Ce Zhang at ETH Zurich. My research focus on speeding up machine learning systems and making them more accessible to users. Prior to joining ETH as a Ph.D student, I got my Master's degree in Computer Science at ETH Zurich in 2017 and my Bachelor's degree in Machine Intelligence at Peking University in 2014.
News
- June.15th, 2018: I am really excited to be a intern with Umar Farooq Minhas at Databse Group, Microsoft Research Redmond working on updatable learned index this summer.
- May.18th, 2018: Our work "MLBench: Benchmarking Machine Learning Services Against Human Experts" is accepted at VLDB 2018.
- Mar.20th, 2018: Our work "PSFGAN: a generative adversarial network system for separating quasar point sources and host galaxy light" is accepted by Monthly Notices of the Royal Astronomical Society (MNRAS).
- Aug.10th, 2017: I presented our ZipML paper at ICML 2017.
- Jun.26th, 2017: Our work "Scalable Inference of Decision Tree Ensembles: Flexible Design for CPU-FPGA Platforms" is accepted at FPL 2017.
- Jun.20th, 2017: I got ICML travel award for this year. Big thank you to ICML commitee!
- May.12th, 2017: Our ZipML work "The ZipML Framework for Training Models with End-to-End Low Precision: The Cans, the Cannots, and a Little Bit of Deep Learning" is accepted at ICML 2017
- May.10th, 2017: I gave a talk "Faster Machine Learning via Low-Precision Communication and Computation" with Dan Alistarh at Nvidia GPU Technology Conference (GTC) 2017.
Publications
Generative adversarial networks recover features in astrophysical images of galaxies beyond the deconvolution limit.
Ce Zhang, Kevin Schawinski,Hantian Zhang, Lucas Fowler, Gokula Krishnan Santhanam
MNRAS 2017
Scalable Inference of Decision Tree Ensembles: Flexible Design for CPU-FPGA Platforms
Muhsen Owaida, Hantian Zhang, Ce Zhang, Gustavo Alonso
FPL 2017
MLBench: Benchmarking Machine Learning Services Against Human Experts
Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang
VLDB 2018
Generative adversarial networks as a tool to recover structural information from cryo-electron microscopy data
Min Su, Hantian Zhang, Kevin Schawinski, Ce Zhang, Michael A Cianfrocco
bioRxiv 2018
PSFGAN: a generative adversarial network system for separating quasar point sources and host galaxy light
Dominic Stark, Barthelemy Launet, Kevin Schawinski, Ce Zhang, Michael Koss, M Dennis Turp, Lia F Sartori, Hantian Zhang, Yiru Chen, Anna K Weigel.
MNRAS 2018
Education
- Ph.D. Student, ETH Zurich, 2017.5 - Present
- M.S., ETH Zurich, 2014.9 - 2017.4
- B.S., Peking University, 2010.9 - 2014.6