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ORCIDCe Zhang 0001
Person information
- affiliation: ETH Zurich, Institut für Computing Platforms, Switzerland
- affiliation (former): Stanford University, Computer Science Department, CA, USA
- affiliation (former): University of Wisconsin-Madison, Department of Computer Science, Madison, WI, USA
- affiliation (former): Peking University, Beijing, China
Other persons with the same name
- Ce Zhang — disambiguation page
- Ce Zhang 0002 — Renmin University of China, School of Information, Beijing, China
- Ce Zhang 0003 — Shenyang Ligong University, School of Information Science and Engineering, China
- Ce Zhang 0004
![[0000-0001-5571-9766]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-5571-9766")
(aka: Delvin Ce Zhang) — Singapore Management University, Singapore - Ce Zhang 0005 — University of Bristol, School of Geographical Sciences, UK (and 1 more)
- Ce Zhang 0006 — Chinese Academy of Sciences, Institute of Automation, Interactive Digital Media Technology Research Center, Beijing, China
- Ce Zhang 0007 — Hong Kong Baptist University, China
- Ce Zhang 0008 — Virginia Tech, Blacksburg, VA, USA
- Ce Zhang 0009 — Carnegie Mellon University, Machine Learning Department, Pittsburgh, PA, USA
- Ce Zhang 0010 — University of North Carolina at Chapel Hill, NC, USA
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2020 – today
- 2024
[j51]Stefan Grafberger, Zeyu Zhang, Sebastian Schelter, Ce Zhang:
Red Onions, Soft Cheese and Data: From Food Safety to Data Traceability for Responsible AI. IEEE Data Eng. Bull. 47(1): 63-81 (2024)- [j50]Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu, Sixian Du, Wentao Zhang, Ce Zhang, Bin Cui:
OpenBox: A Python Toolkit for Generalized Black-box Optimization. J. Mach. Learn. Res. 25: 120:1-120:11 (2024) - [j49]Jiawei Jiang, Shaoduo Gan, Bo Du, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Sheng Wang, Ce Zhang:
A systematic evaluation of machine learning on serverless infrastructure. VLDB J. 33(2): 425-449 (2024) - [j48]Jiawei Jiang, Yi Wei, Yu Liu, Wentao Wu, Chuang Hu, Zhigao Zheng, Ziyi Zhang, Yingxia Shao, Ce Zhang:
How good are machine learning clouds? Benchmarking two snapshots over 5 years. VLDB J. 33(3): 833-857 (2024) - [j47]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems. VLDB J. 33(5): 1231-1255 (2024) - [c141]Steve Rhyner, Haocong Luo, Juan Gómez-Luna, Mohammad Sadrosadati, Jiawei Jiang, Ataberk Olgun, Harshita Gupta, Ce Zhang, Onur Mutlu:
PIM-Opt: Demystifying Distributed Optimization Algorithms on a Real-World Processing-In-Memory System. PACT 2024: 201-218 - [c140]Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang:
Data Debugging with Shapley Importance over Machine Learning Pipelines. ICLR 2024 - [c139]Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song:
Effective and Efficient Federated Tree Learning on Hybrid Data. ICLR 2024 - [c138]Michael Poli, Armin W. Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli:
Mechanistic Design and Scaling of Hybrid Architectures. ICML 2024 - [c137]Chulin Xie, Pin-Yu Chen, Qinbin Li, Arash Nourian, Ce Zhang, Bo Li:
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM. SaTML 2024: 443-471 - [c136]Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang:
MS MARCO Web Search: A Large-scale Information-rich Web Dataset with Millions of Real Click Labels. WWW (Companion Volume) 2024: 292-301 - [i140]Lijie Xu, Chulin Xie, Yiran Guo, Gustavo Alonso, Bo Li, Guoliang Li, Wei Wang, Wentao Wu, Ce Zhang:
TablePuppet: A Generic Framework for Relational Federated Learning. CoRR abs/2403.15839 (2024) - [i139]Michael Poli, Armin W. Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli:
Mechanistic Design and Scaling of Hybrid Architectures. CoRR abs/2403.17844 (2024) - [i138]Steve Rhyner, Haocong Luo, Juan Gómez-Luna, Mohammad Sadrosadati, Jiawei Jiang, Ataberk Olgun, Harshita Gupta, Ce Zhang, Onur Mutlu:
Analysis of Distributed Optimization Algorithms on a Real Processing-In-Memory System. CoRR abs/2404.07164 (2024) - [i137]Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang:
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels. CoRR abs/2405.07526 (2024) - [i136]Josh Veitch-Michaelis, Andrew Cottam, Daniella Schweizer, Eben N. Broadbent, David Dao, Ce Zhang, Angelica Almeyda Zambrano, Simeon Max:
OAM-TCD: A globally diverse dataset of high-resolution tree cover maps. CoRR abs/2407.11743 (2024) - [i135]Baijun Cheng, Ce Zhang, Kailong Wang, Ling Shi, Yang Liu, Haoyu Wang, Yao Guo, Xiangqun Chen:
Semantic-Enhanced Indirect Call Analysis with Large Language Models. CoRR abs/2408.04344 (2024) - 2023
- [j46]Yujing Wang, Yaming Yang, Zhuo Li, Jiangang Bai, Mingliang Zhang, Xiangtai Li, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong:
Convolution-Enhanced Evolving Attention Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8176-8192 (2023) - [j45]Yang Li, Huaijun Jiang, Yu Shen, Yide Fang, Xiaofeng Yang, Danqing Huang, Xinyi Zhang, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui:
Towards General and Efficient Online Tuning for Spark. Proc. VLDB Endow. 16(12): 3570-3583 (2023) - [j44]Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang:
Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture. IEEE Trans. Knowl. Data Eng. 35(2): 1721-1733 (2023) - [j43]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023) - [j42]Yang Li, Yu Shen, Wentao Zhang, Ce Zhang, Bin Cui:
VolcanoML: speeding up end-to-end AutoML via scalable search space decomposition. VLDB J. 32(2): 389-413 (2023) - [c135]Cédric Renggli, Luka Rimanic, Luka Kolar, Wentao Wu, Ce Zhang:
Automatic Feasibility Study via Data Quality Analysis for ML: A Case-Study on Label Noise. ICDE 2023: 218-231 - [c134]Guangyu Zhang, Chunhua Li, Ke Zhou, Li Liu, Ce Zhang, Wancheng Chen, Haotian Fang, Bin Cheng, Jie Yang, Jiashu Xing:
DBCatcher: A Cloud Database Online Anomaly Detection System based on Indicator Correlation. ICDE 2023: 1126-1139 - [c133]Johannes Rausch, Gentiana Rashiti, Maxim Gusev, Ce Zhang, Stefan Feuerriegel:
DSG: An End-to-End Document Structure Generator. ICDM 2023: 518-527 - [c132]Yilmazcan Özyurt, Stefan Feuerriegel, Ce Zhang:
Contrastive Learning for Unsupervised Domain Adaptation of Time Series. ICLR 2023 - [c131]Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen:
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. ICML 2023: 22137-22176 - [c130]Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang:
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. ICML 2023: 31094-31116 - [c129]Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li:
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization. ICML 2023: 35908-35948 - [c128]Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher Ré, Ce Zhang:
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks. ICML 2023: 36058-36076 - [c127]Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré:
Skill-it! A data-driven skills framework for understanding and training language models. NeurIPS 2023 - [c126]Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio:
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. NeurIPS 2023 - [c125]Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi:
DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS 2023 - [c124]Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang:
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. NeurIPS 2023 - [c123]Jiawei Zhang, Linyi Li, Ce Zhang, Bo Li:
CARE: Certifiably Robust Learning with Reasoning via Variational Inference. SaTML 2023: 554-574 - [c122]Sebastian Schelter, Stefan Grafberger, Shubha Guha, Bojan Karlas, Ce Zhang:
Proactively Screening Machine Learning Pipelines with ARGUSEYES. SIGMOD Conference Companion 2023: 91-94 - [c121]Maurice Weber, Xiaojun Xu, Bojan Karlas, Ce Zhang, Bo Li:
RAB: Provable Robustness Against Backdoor Attacks. SP 2023: 1311-1328 - [e1]Ana Gainaru, Ce Zhang, Chunjie Luo:
Benchmarking, Measuring, and Optimizing - 14th BenchCouncil International Symposium, Bench 2022, Virtual Event, November 7-9, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13852, Springer 2023, ISBN 978-3-031-31179-6 [contents] - [i134]Susie Xi Rao, Peter H. Egger, Ce Zhang:
Hierarchical Classification of Research Fields in the "Web of Science" Using Deep Learning. CoRR abs/2302.00390 (2023) - [i133]Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang:
High-throughput Generative Inference of Large Language Models with a Single GPU. CoRR abs/2303.06865 (2023) - [i132]Huaijun Jiang, Yu Shen, Yang Li, Wentao Zhang, Ce Zhang, Bin Cui:
OpenBox: A Python Toolkit for Generalized Black-box Optimization. CoRR abs/2304.13339 (2023) - [i131]Xiaozhong Lyu, Stefan Grafberger, Samantha Biegel, Shaopeng Wei, Meng Cao, Sebastian Schelter, Ce Zhang:
Improving Retrieval-Augmented Large Language Models via Data Importance Learning. CoRR abs/2307.03027 (2023) - [i130]Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré:
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models. CoRR abs/2307.14430 (2023) - [i129]Qiang Huang, Jiawei Jiang, Susie Xi Rao, Ce Zhang, Zhichao Han, Zitao Zhang, Xin Wang, Yongjun He, Quanqing Xu, Yang Zhao, Chuang Hu, Shuo Shang, Bo Du:
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks. CoRR abs/2308.16385 (2023) - [i128]Yang Li, Huaijun Jiang, Yu Shen, Yide Fang, Xiaofeng Yang, Danqing Huang, Xinyi Zhang, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui:
Towards General and Efficient Online Tuning for Spark. CoRR abs/2309.01901 (2023) - [i127]Johannes Rausch, Gentiana Rashiti, Maxim Gusev, Ce Zhang, Stefan Feuerriegel:
DSG: An End-to-End Document Structure Generator. CoRR abs/2310.09118 (2023) - [i126]Yilmazcan Özyurt, Stefan Feuerriegel, Ce Zhang:
In-Context Few-Shot Relation Extraction via Pre-Trained Language Models. CoRR abs/2310.11085 (2023) - [i125]Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song:
Effective and Efficient Federated Tree Learning on Hybrid Data. CoRR abs/2310.11865 (2023) - [i124]Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen:
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. CoRR abs/2310.17157 (2023) - [i123]Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, Aman Timalsina, David W. Romero, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio:
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. CoRR abs/2310.18780 (2023) - [i122]Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson:
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR abs/2311.13028 (2023) - [i121]Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang:
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. CoRR abs/2312.10188 (2023) - 2022
- [b1]Jiawei Jiang, Bin Cui, Ce Zhang:
Distributed Machine Learning and Gradient Optimization. Springer 2022, ISBN 978-981-16-3419-2, pp. 1-169 - [j41]Stefan Feuerriegel, Yash Raj Shrestha, Georg von Krogh, Ce Zhang:
Bringing artificial intelligence to business management. Nat. Mach. Intell. 4(7): 611-613 (2022) - [j40]Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mach. Intell. 4(8): 669-677 (2022) - [j39]Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mac. Intell. 4(10): 904 (2022) - [j38]Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui:
Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. Proc. VLDB Endow. 15(6): 1256-1265 (2022) - [j37]Cédric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang:
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning. Proc. VLDB Endow. 16(2): 304-316 (2022) - [j36]Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, K. Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos:
Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. SIGMOD Rec. 51(2): 30-37 (2022) - [c120]Susie Xi Rao, Johannes Rausch, Peter H. Egger, Ce Zhang:
TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets. SDU@AAAI 2022 - [c119]Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Kenza Amara, Attila Steinegger, Ce Zhang, Xiaoxiang Zhu:
ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery. AAAI 2022: 12119-12125 - [c118]Patrick Damme, Marius Birkenbach, Constantinos Bitsakos, Matthias Boehm, Philippe Bonnet, Florina M. Ciorba, Mark Dokter, Pawel Dowgiallo, Ahmed Eleliemy, Christian Faerber, Georgios I. Goumas, Dirk Habich, Niclas Hedam, Marlies Hofer, Wenjun Huang, Kevin Innerebner, Vasileios Karakostas, Roman Kern, Tomaz Kosar, Alexander Krause, Daniel Krems, Andreas Laber, Wolfgang Lehner, Eric Mier, Marcus Paradies, Bernhard Peischl, Gabrielle Poerwawinata, Stratos Psomadakis, Tilmann Rabl, Piotr Ratuszniak, Pedro Silva, Nikolai Skuppin, Andreas Starzacher, Benjamin Steinwender, Ilin Tolovski, Pinar Tözün, Wojciech Ulatowski, Yuanyuan Wang, Izajasz P. Wrosz, Ales Zamuda, Ce Zhang, Xiaoxiang Zhu:
DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines. CIDR 2022 - [c117]Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang:
Screening Native Machine Learning Pipelines with ArgusEyes. CIDR 2022 - [c116]Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang:
BRIGHT - Graph Neural Networks in Real-time Fraud Detection. CIKM 2022: 3342-3351 - [c115]Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic:
Which Model to Transfer? Finding the Needle in the Growing Haystack. CVPR 2022: 9195-9204 - [c114]Sabri Eyuboglu, Bojan Karlas, Christopher Ré, Ce Zhang, James Zou:
dcbench: a benchmark for data-centric AI systems. DEEM@SIGMOD 2022: 9:1-9:4 - [c113]Han Zhang, Zhefan Yu, Ce Zhang, Ruotian Zhang, Yuyang Liu, Seung Hee Lee:
User-Centered Information Architecture of Vehicle AR-HUD Interface. HCI (34) 2022: 309-325 - [c112]Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang:
Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). ICDE 2022: 1561-1562 - [c111]Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang:
Neural Methods for Logical Reasoning over Knowledge Graphs. ICLR 2022 - [c110]Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding:
iFlood: A Stable and Effective Regularizer. ICLR 2022 - [c109]Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang:
Certifying Out-of-Domain Generalization for Blackbox Functions. ICML 2022: 23527-23548 - [c108]Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, Bin Cui:
TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning. KDD 2022: 956-966 - [c107]Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, Bin Cui:
Transfer Learning based Search Space Design for Hyperparameter Tuning. KDD 2022: 967-977 - [c106]Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu:
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. KDD 2022: 3288-3298 - [c105]Kenza Amara, Zhitao Ying, Zitao Zhang, Zhichao Han, Yang Zhao, Yinan Shan, Ulrik Brandes, Sebastian Schemm, Ce Zhang:
GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks. LoG 2022: 44 - [c104]Thórhildur Thorleiksdóttir, Cédric Renggli, Nora Hollenstein, Ce Zhang:
Dynamic Human Evaluation for Relative Model Comparisons. LREC 2022: 5946-5955 - [c103]Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang:
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? NeurIPS 2022 - [c102]Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li:
Certifying Some Distributional Fairness with Subpopulation Decomposition. NeurIPS 2022 - [c101]Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang:
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees. NeurIPS 2022 - [c100]Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlas, Ji Liu, Heng Guo, Ce Zhang, Bo Li:
Improving Certified Robustness via Statistical Learning with Logical Reasoning. NeurIPS 2022 - [c99]Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang:
Decentralized Training of Foundation Models in Heterogeneous Environments. NeurIPS 2022 - [c98]Baoqing Cai, Yu Liu, Ce Zhang, Guangyu Zhang, Ke Zhou, Li Liu, Chunhua Li, Bin Cheng, Jie Yang, Jiashu Xing:
HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements. SIGMOD Conference 2022: 646-659 - [c97]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference 2022: 1286-1300 - [c96]Fan Wu, Yunhui Long, Ce Zhang, Bo Li:
LINKTELLER: Recovering Private Edges from Graph Neural Networks via Influence Analysis. SP 2022: 2005-2024 - [c95]Susie Xi Rao, Piriyakorn Piriyatamwong, Parijat Ghoshal, Sara Nasirian, Sandra Mitrovic, Emmanuel de Salis, Michael Wechner, Vanya Brucker, Peter H. Egger, Ce Zhang:
Keyword Extraction in Scientific Documents. SwissText 2022: 44-55 - [c94]Yilmazcan Özyurt, Tobias Hatt, Ce Zhang, Stefan Feuerriegel:
A Deep Markov Model for Clickstream Analytics in Online Shopping. WWW 2022: 3071-3081 - [r1]Shuai Zhang, Yi Tay, Lina Yao, Aixin Sun, Ce Zhang:
Deep Learning for Recommender Systems. Recommender Systems Handbook 2022: 173-210 - [d1]Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang:
schelterlabs/arguseyes. Zenodo, 2022
- [i120]Susie Xi Rao, Johannes Rausch, Peter H. Egger, Ce Zhang:
TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets. CoRR abs/2201.01654 (2022) - [i119]Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui:
Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. CoRR abs/2201.06834 (2022) - [i118]Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Kenza Amara, Attila Steinegger, Ce Zhang, Xiaoxiang Zhu:
ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery. CoRR abs/2201.11192 (2022) - [i117]Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang:
Certifying Out-of-Domain Generalization for Blackbox Functions. CoRR abs/2202.01679 (2022) - [i116]Leonel Aguilar, Michal Gath-Morad, Jascha Grübel, Jasper Ermatinger, Hantao Zhao, Stefan Wehrli, Robert W. Sumner, Ce Zhang, Dirk Helbing, Christoph Hölscher:
Experiments as Code: A Concept for Reproducible, Auditable, Debuggable, Reusable, & Scalable Experiments. CoRR abs/2202.12050 (2022) - [i115]Cédric Renggli, Xiaozhe Yao, Luka Kolar, Luka Rimanic, Ana Klimovic, Ce Zhang:
SHiFT: An Efficient, Flexible Search Engine for Transfer Learning. CoRR abs/2204.01457 (2022) - [i114]Susie Xi Rao, Clémence Lanfranchi, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, Ce Zhang:
Modelling graph dynamics in fraud detection with "Attention". CoRR abs/2204.10614 (2022) - [i113]Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang:
Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. CoRR abs/2204.11131 (2022) - [i112]Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang:
BRIGHT - Graph Neural Networks in Real-Time Fraud Detection. CoRR abs/2205.13084 (2022) - [i111]Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li:
Certifying Some Distributional Fairness with Subpopulation Decomposition. CoRR abs/2205.15494 (2022) - [i110]Binhang Yuan, Yongjun He, Jared Quincy Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang:
Decentralized Training of Foundation Models in Heterogeneous Environments. CoRR abs/2206.01288 (2022) - [i109]Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang:
Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees. CoRR abs/2206.01299 (2022) - [i108]Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, Bin Cui:
Transfer Learning based Search Space Design for Hyperparameter Tuning. CoRR abs/2206.02511 (2022) - [i107]Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, Bin Cui:
TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning. CoRR abs/2206.02663 (2022) - [i106]Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li:
FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization. CoRR abs/2206.03966 (2022) - [i105]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic Gradient Descent without Full Data Shuffle. CoRR abs/2206.05830 (2022) - [i104]Yilmazcan Özyurt, Stefan Feuerriegel, Ce Zhang:
Contrastive Learning for Unsupervised Domain Adaptation of Time Series. CoRR abs/2206.06243 (2022) - [i103]