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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://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-5571-9766")
(aka: Delvin Ce Zhang) — Singapore Management University, Singapore - Ce Zhang 0005 — Lancaster University, Environment Centre, UK
- 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
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2020 – today
- 2023
[j43]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)- [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) - [i121]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) - [i120]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) - 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) - [c117]Susie Xi Rao, Johannes Rausch, Peter H. Egger, Ce Zhang:
TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets. SDU@AAAI 2022 - [c116]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 - [c115]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 - [c114]Sebastian Schelter, Stefan Grafberger, Shubha Guha, Olivier Sprangers, Bojan Karlas, Ce Zhang:
Screening Native Machine Learning Pipelines with ArgusEyes. CIDR 2022 - [c113]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 - [c112]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 - [c111]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 - [c110]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 - [c109]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 - [c108]Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang:
Neural Methods for Logical Reasoning over Knowledge Graphs. ICLR 2022 - [c107]Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding:
iFlood: A Stable and Effective Regularizer. ICLR 2022 - [c106]Maurice Weber, Linyi Li, Boxin Wang, Zhikuan Zhao, Bo Li, Ce Zhang:
Certifying Out-of-Domain Generalization for Blackbox Functions. ICML 2022: 23527-23548 - [c105]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 - [c104]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 - [c103]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 - [c102]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 - [c101]Thórhildur Thorleiksdóttir, Cédric Renggli, Nora Hollenstein, Ce Zhang:
Dynamic Human Evaluation for Relative Model Comparisons. LREC 2022: 5946-5955 - [c100]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 - [c99]Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li:
Certifying Some Distributional Fairness with Subpopulation Decomposition. NeurIPS 2022 - [c98]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 - [c97]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 - [c96]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 - [c95]Fan Wu, Yunhui Long, Ce Zhang, Bo Li:
LINKTELLER: Recovering Private Edges from Graph Neural Networks via Influence Analysis. IEEE Symposium on Security and Privacy 2022: 2005-2024 - [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 - [i119]Susie Xi Rao, Johannes Rausch, Peter H. Egger, Ce Zhang:
TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets. CoRR abs/2201.01654 (2022) - [i118]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) - [i117]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) - [i116]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) - [i115]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) - [i114]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) - [i113]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) - [i112]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) - [i111]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) - [i110]Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li:
Certifying Some Distributional Fairness with Subpopulation Decomposition. CoRR abs/2205.15494 (2022) - [i109]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) - [i108]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) - [i107]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) - [i106]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) - [i105]Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li:
FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization. CoRR abs/2206.03966 (2022) - [i104]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) - [i103]Yilmazcan Özyurt, Stefan Feuerriegel, Ce Zhang:
Contrastive Learning for Unsupervised Domain Adaptation of Time Series. CoRR abs/2206.06243 (2022) - [i102]Yang Li, Yu Shen, Wentao Zhang, Ce Zhang, Bin Cui:
Efficient End-to-End AutoML via Scalable Search Space Decomposition. CoRR abs/2206.09423 (2022) - [i101]Kenza Amara, Rex Ying, Zitao Zhang, Zhihao Han, Yinan Shan, Ulrik Brandes, Sebastian Schemm, Ce Zhang:
GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks. CoRR abs/2206.09677 (2022) - [i100]Susie Xi Rao, Piriyakorn Piriyatamwong, Parijat Ghoshal, Sara Nasirian, Emmanuel de Salis, Sandra Mitrovic, Michael Wechner, Vanya Brucker, Peter H. Egger, Ce Zhang:
Keyword Extraction in Scientific Documents. CoRR abs/2207.01888 (2022) - [i99]Chulin Xie, Pin-Yu Chen, Ce Zhang, Bo Li:
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM. CoRR abs/2207.10226 (2022) - [i98]Simon Kassing, Vojislav Dukic, Ce Zhang, Ankit Singla:
New primitives for bounded degradation in network service. CoRR abs/2208.08429 (2022) - [i97]Jiawei Zhang, Linyi Li, Ce Zhang, Bo Li:
CARE: Certifiably Robust Learning with Reasoning via Variational Inference. CoRR abs/2209.05055 (2022) - [i96]Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang:
Neural Methods for Logical Reasoning Over Knowledge Graphs. CoRR abs/2209.14464 (2022) - [i95]Yangheng Zhao, Jun Wang, Xiaolong Li, Yue Hu, Ce Zhang, Yanfeng Wang, Siheng Chen:
Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation. CoRR abs/2210.09948 (2022) - [i94]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. CoRR abs/2211.09110 (2022) - [i93]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. CoRR abs/2212.08330 (2022) - 2021
- [j35]Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang:
A Data Quality-Driven View of MLOps. IEEE Data Eng. Bull. 44(1): 11-23 (2021) - [j34]Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Yaliang Li, Bolin Ding, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui:
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. Proc. VLDB Endow. 14(11): 2167-2176 (2021) - [j33]Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim, Artidoro Pagnoni, Ce Zhang, Byung-Gon Chun, Markus Weimer, Matteo Interlandi:
WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele. Proc. VLDB Endow. 15(1): 11-20 (2021) - [j32]Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Zhiyao Chen, Yinan Shan, Yang Zhao, Ce Zhang:
xFraud: Explainable Fraud Transaction Detection. Proc. VLDB Endow. 15(3): 427-436 (2021) - [j31]Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang:
BAGUA: Scaling up Distributed Learning with System Relaxations. Proc. VLDB Endow. 15(4): 804-813 (2021) - [j30]Zitao Li, Bolin Ding, Ce Zhang, Ninghui Li, Jingren Zhou:
Federated Matrix Factorization with Privacy Guarantee. Proc. VLDB Endow. 15(4): 900-913 (2021) - [j29]Heqing Huang, Cong Zheng, Junyuan Zeng, Wu Zhou, Sencun Zhu, Peng Liu, Ian M. Molloy, Suresh Chari, Ce Zhang, Quanlong Guan:
A Large-Scale Study of Android Malware Development Phenomenon on Public Malware Submission and Scanning Platform. IEEE Trans. Big Data 7(2): 255-270 (2021) - [j28]Yunyan Guo, Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Bin Cui, Jianzhong Li:
Model averaging in distributed machine learning: a case study with Apache Spark. VLDB J. 30(4): 693-712 (2021) - [c93]Johannes Rausch, Octavio Martinez, Fabian Bissig, Ce Zhang, Stefan Feuerriegel:
DocParser: Hierarchical Document Structure Parsing from Renderings. AAAI 2021: 4328-4338 - [c92]Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang, Bin Cui:
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements. AAAI 2021: 8491-8500 - [c91]Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause:
Online Active Model Selection for Pre-trained Classifiers. AISTATS 2021: 307-315 - [c90]Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Bhavya Kailkhura, Tao Xie, Ce Zhang, Bo Li:
TSS: Transformation-Specific Smoothing for Robustness Certification. CCS 2021: 535-557 - [c89]Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li:
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CCS 2021: 2146-2168 - [c88]Leonel Aguilar Melgar, David Dao, Shaoduo Gan, Nezihe Merve Gürel, Nora Hollenstein, Jiawei Jiang, Bojan Karlas, Thomas Lemmin, Tian Li, Yang Li, Susie Xi Rao, Johannes Rausch, Cédric Renggli, Luka Rimanic, Maurice Weber, Shuai Zhang, Zhikuan Zhao, Kevin Schawinski, Wentao Wu, Ce Zhang:
Ease.ML: A Lifecycle Management System for Machine Learning. CIDR 2021 - [c87]Yaliang Li, Zhen Wang, Yuexiang Xie, Bolin Ding, Kai Zeng, Ce Zhang:
AutoML: From Methodology to Application. CIKM 2021: 4853-4856 - [c86]Ruoxi Jia, Fan Wu, Xuehui Sun, Jiacen Xu, David Dao, Bhavya Kailkhura, Ce Zhang, Bo Li, Dawn Song:
Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification? CVPR 2021: 8239-8247 - [c85]Peng Li, Xi Rao, Jennifer Blase, Yue Zhang, Xu Chu, Ce Zhang:
CleanML: A Study for Evaluating the Impact of Data Cleaning on ML Classification Tasks. ICDE 2021: 13-24 - [c84]Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li:
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks. ICML 2021: 3976-3987 - [c83]Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He:
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed. ICML 2021: 10118-10129 - [c82]Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong:
Evolving Attention with Residual Convolutions. ICML 2021: 10971-10980 - [c81]Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Susie Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang:
DeGNN: Improving Graph Neural Networks with Graph Decomposition. KDD 2021: 1223-1233 - [c80]Wenqi Jiang, Zhenhao He, Shuai Zhang, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso:
FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters. KDD 2021: 3097-3105 - [c79]Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui:
OpenBox: A Generalized Black-box Optimization Service. KDD 2021: 3209-3219 - [c78]Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou:
FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data. KDD 2021: 3795-3805 - [c77]Yaliang Li, Zhen Wang, Bolin Ding, Ce Zhang:
AutoML: A Perspective where Industry Meets Academy. KDD 2021: 4048-4049 - [c76]Wenqi Jiang, Zhenhao He, Shuai Zhang, Thomas B. Preußer, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso:
MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions. MLSys 2021 - [c75]Shuai Zhang, Xi Rao, Yi Tay, Ce Zhang:
Knowledge Router: Learning Disentangled Representations for Knowledge Graphs. NAACL-HLT 2021: 1-10 - [c74]Nora Hollenstein, Federico Pirovano, Ce Zhang, Lena A. Jäger, Lisa Beinborn:
Multilingual Language Models Predict Human Reading Behavior. NAACL-HLT 2021: 106-123 - [c73]Cédric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang:
Evaluating Bayes Error Estimators on Real-World Datasets with FeeBee. NeurIPS Datasets and Benchmarks 2021 - [c72]Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li:
TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness. NeurIPS 2021: 17642-17655 - [c71]Wentao Wu, Ce Zhang:
Towards understanding end-to-end learning in the context of data: machine learning dancing over semirings & Codd's table. DEEM@SIGMOD 2021: 1:1-1:4 - [c70]Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang:
Towards Demystifying Serverless Machine Learning Training. SIGMOD Conference 2021: 857-871 - [c69]Shuai Zhang, Huoyu Liu, Aston Zhang, Yue Hu, Ce Zhang, Yumeng Li, Tanchao Zhu, Shaojian He, Wenwu Ou:
Learning User Representations with Hypercuboids for Recommender Systems. WSDM 2021: 716-724 - [i92]Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He:
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed. CoRR abs/2102.02888 (2021) - [i91]Cédric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlas, Wentao Wu, Ce Zhang:
A Data Quality-Driven View of MLOps. CoRR abs/2102.07750 (2021) - [i90]Nora Hollenstein, Cédric Renggli, Benjamin Glaus, Maria Barrett, Marius Troendle, Nicolas Langer, Ce Zhang:
Decoding EEG Brain Activity for Multi-Modal Natural Language Processing. CoRR abs/2102.08655 (2021) - [i89]Shuai Zhang, Yi Tay, Wenqi Jiang, Da-Cheng Juan, Ce Zhang:
Switch Spaces: Learning Product Spaces with Sparse Gating. CoRR abs/2102.08688 (2021) - [i88]Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong:
Evolving Attention with Residual Convolutions. CoRR abs/2102.12895 (2021) - [i87]Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang:
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting. CoRR abs/2103.07719 (2021) - [i86]Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li:
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CoRR abs/2103.11109 (2021) - [i85]Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li:
TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness. CoRR abs/2104.00671 (2021) - [i84]Ji Liu, Ce Zhang:
Distributed Learning Systems with First-order Methods. CoRR abs/2104.05245 (2021) - [i83]Nora Hollenstein, Federico Pirovano, Ce Zhang, Lena A. Jäger, Lisa Beinborn:
Multilingual Language Models Predict Human Reading Behavior. CoRR abs/2104.05433 (2021) - [i82]Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang:
Towards Demystifying Serverless Machine Learning Training. CoRR abs/2105.07806 (2021) - [i81]