Zhaozhuo Xu
Email: zxu79 at stevens dot edu
[Scholar][Github]
I am starting as an Assistant Professor of Computer Science at Stevens Institute of Technology in Spring 2024. I also closely collaborate with FEDML.
I received my Ph.D. in Computer Science from Rice University under the supervision of professor Anshumali Shrivastava. My research focuses on scaling up machine learning on commodity hardware using randomized algorithms.
I am organizing the Research On Algorithms & Data Structures (ROADS) to Mega-AI Models Workshop at MLSys! Link
Selected Publication
* indicates equal contribution
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Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis and Anshumali Shrivastava, "Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time", NeurIPS 2023. PDF
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Zichang Liu*, Zhaozhuo Xu*, Benjamin Coleman and Anshumali Shrivastava, "One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning", NeurIPS 2023. PDF
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Zirui Liu*, Guanchu Wang*, Shaochen Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang Tang, Zhimeng Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu and Xia Hu, "Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model", NeurIPS 2023. PDF
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Tianyi Zhang, Zhenwei Dai, Zhaozhuo Xu and Anshumali Shrivastava, "Graph Self-supervised Learning via Proximity Divergence Minimization", UAI 2023. PDF Code
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Zhuang Wang, Xinyu Wu, Zhaozhuo Xu and T. S. Eugene Ng, "Cupcake: A Compression Scheduler for Scalable Communication-Efficient Distributed Training", MLSys 2023. PDF
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Zhaozhuo Xu, Zhao Song and Anshumali Shrivastava, "A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space", AISTATS 2023. PDF
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Tianyi Zhang*, Zhaozhuo Xu*, Tharun Medini and Anshumali Shrivastava, "Structural Contrastive Representation Learning for Zero-shot Multi-label Text Classification", EMNLP Findings 2022. PDF Code
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Zhuang Wang*, Zhaozhuo Xu*, Xinyu Crystal Wu, Anshumali Shrivastava and T. S. Eugene Ng, "DRAGONN: Distributed Randomized Approximate Gradients of Neural Networks", ICML 2022. PDF
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Zichang Liu*, Zhaozhuo Xu*, Alan Ji, Junyan Zhang, Jonathan Li, Beidi Chen and Anshumali Shrivastava, "HALOS: Hashing Large Output Space for Cheap Inference", MLSys 2022. PDF
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Zhaozhuo Xu, Zhao Song and Anshumali Shrivastava, "Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures", NeurIPS 2021. PDF
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Zhaozhuo Xu, Beidi Chen, Chaojian Li, Weiyang Liu, Le Song, Yingyan Lin and Anshumali Shrivastava, "Locality Sensitive Teaching", NeurIPS 2021. PDF Code
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Aditya Desai*, Zhaozhuo Xu*, Menal Gupta, Anu Chandran, Antoine Vial-Aussavy and Anshumali Shrivastava, "Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler", NeurIPS 2021. PDF
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Shulong Tan, Zhaozhuo Xu, Weijie Zhao, Hongliang Fei, Zhixin Zhou and Ping Li, "Norm Adjusted Proximity Graph for Fast Inner Product Retrieval", KDD 2021. PDF
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Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava and Christopher Re, "MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training ", ICLR 2021 Oral. PDF Code
- Shulong Tan, Zhixin Zhou, Zhaozhuo Xu and Ping Li, "Fast Item Ranking under Neural Network based Measures", WSDM 2020. PDF
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Zhaozhuo Xu, Alan Baonan Ji, Andrew Woods, Beidi Chen and Anshumali Shrivastava, "Satellite Images and Deep Learning to Identify Discrepancy in Mailing Addresses with Applications to Census 2020 in Houston", JSM 2020. PDF
- Zhixin Zhou, Shulong Tan, Zhaozhuo Xu and Ping Li, "Möbius Transformation for Fast Inner Product Search on Graph", NeurIPS 2019. PDF Code
- Shulong Tan, Zhixin Zhou, Zhaozhuo Xu and Ping Li, "On Efficient Retrieval of Top Similarity Vectors", EMNLP 2019. PDF
Honor
- Ken Kennedy Institute BP Fellowship, 2021 - 2022. Link