Email: zywu at berkeley dot edu/ zw287 at cornell dot edu (old) Google Scholar
I am a first-year Ph.D. student advised by Prof. Yi Ma at UC Berkeley. I obtained my MS degree at Cornell University advised by Prof. Bharath Hariharan and Prof. Madeleine Udell. I graduated summa cum laude and received my BS degrees from Cornell University in Computer Science and in Operations Research. I also spent one year working as a researcher advised by Prof. Harry Shum at International Digital Economy Academy (IDEA) in Shenzhen, China. My primary research interests lie in machine learning and computer vision.
(* indicates equal contribution)
Incremental Learning of Structured Memory via Closed-Loop Transcription Shengbang Tong, Xili Dai, Ziyang Wu , Mingyang Li, Brent Yi, Yi Ma [arxiv]
Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction Xili Dai*, Shengbang Tong*, Mingyang Li*, Ziyang Wu* , Kwan Ho Ryan Chan, Pengyuan Zhai, Yaodong Yu, Michael Psenka, Xiaojun Yuan, Heung-Yeung Shum, Yi Ma MDPI Entropy [link] [arxiv]
Efficient Maximal Coding Rate Reduction by Variational Forms Christina Baek*, Ziyang Wu*, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin Haeffele Conference of Computer Vision and Pattern Recognition (CVPR), 2022 [link]
How Low Can We Go: Trading Memory for Error in Low-Precision Training Chengrun Yang*, Ziyang Wu* , Jerry Chee, Christopher De Sa, Madeleine Udell International Conference on Learning Representations (ICLR), 2022 [link] [arxiv] [code]
Incremental Learning via Rate Reduction Ziyang Wu* , Christina Baek*, Chong You, Yi Ma Conference of Computer Vision and Pattern Recognition (CVPR), 2021 ICML Workshop on Theory and Foundation of Continual Learning, 2021 (Oral Presentation) [arxiv]
Can We Characterize Tasks Without Labels or Features Bram Wallace*, Ziyang Wu* , Bharath Hariharan Conference of Computer Vision and Pattern Recognition (CVPR), 2021 [link] [code]
TenIPS: Inverse Propensity Sampling for Tensor Completion Chengrun Yang, Lijun Ding, Ziyang Wu , Madeleine Udell NeurIPS 2020 Workshop on Optimization for Machine Learning (OPT), 2020 (Oral Presentation) International Conference on Artificial Intelligence and Statistics (AISTATS), 2021 [arxiv]
AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space Chengrun Yang, Jicong Fan, Ziyang Wu , Madeleine Udell ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 [link] [code]
Automated Machine Learning and Task Space Navigation Ziyang Wu Master’s Thesis, Cornell University, 2021 [link]
Maximizing Rate Reduction: Principle and Applications International Digital Economy Academy (IDEA), Oct. 2021
Incremental Learning via Rate Reduction ICML Workshop on Theory and Foundation of Continual Learning, Jul. 2021 [link]
CS 4700 (Fall 2018, Fall 2019, Fall 2020): Foundations of Artificial Intelligence (Teaching Assistant)
CS 2800 (Fall 2016, Spring 2021): Discrete Structures (Teaching Assistant)
CS 4670/5670 (Spring 2020): Introduction to Computer Vision (Teaching Assistant)
CS 4820 (Fall 2017, Summer 2020): Introduction to Algorithms (Teaching Assistant)
CS 3110 (Spring 2017): Data Structures and Functional Programming (Teaching Assistant)
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