Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Ce Zhang

Ce Zhang

TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets


Jan 05, 2022
Susie Xi Rao, Johannes Rausch, Peter Egger, Ce Zhang

Figure 1 for TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets
Figure 2 for TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets
Figure 3 for TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets
Figure 4 for TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets
* accepted in the AAAI-22 Workshop on Scientific Document Understanding at the Thirty-Sixth AAAI Conference on Artificial Intelligence ([email protected]) 
  Access Paper or Ask Questions

Super-resolution reconstruction of cytoskeleton image based on A-net deep learning network


Dec 17, 2021
Qian Chen, Haoxin Bai, Bingchen Che, Tianyun Zhao, Ce Zhang, Kaige Wang, Jintao Bai, Wei Zhao

Figure 1 for Super-resolution reconstruction of cytoskeleton image based on A-net deep learning network
Figure 2 for Super-resolution reconstruction of cytoskeleton image based on A-net deep learning network
Figure 3 for Super-resolution reconstruction of cytoskeleton image based on A-net deep learning network
Figure 4 for Super-resolution reconstruction of cytoskeleton image based on A-net deep learning network
* The manuscript has 17 pages, 10 figures and 58 references 
  Access Paper or Ask Questions

Dynamic Human Evaluation for Relative Model Comparisons


Dec 15, 2021
Th贸rhildur Thorleiksd贸ttir, Cedric Renggli, Nora Hollenstein, Ce Zhang

Figure 1 for Dynamic Human Evaluation for Relative Model Comparisons
Figure 2 for Dynamic Human Evaluation for Relative Model Comparisons
Figure 3 for Dynamic Human Evaluation for Relative Model Comparisons
Figure 4 for Dynamic Human Evaluation for Relative Model Comparisons

  Access Paper or Ask Questions

Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters


Nov 23, 2021
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

Figure 1 for Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters
Figure 2 for Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters
Figure 3 for Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters
Figure 4 for Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters

  Access Paper or Ask Questions

Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters


Nov 15, 2021
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

Figure 1 for Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters
Figure 2 for Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters
Figure 3 for Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters
Figure 4 for Persia: A Hybrid System Scaling Deep Learning Based Recommenders up to 100 Trillion Parameters

  Access Paper or Ask Questions

Efficient Hybrid Transformer: Learning Global-local Context for Urban Scene Segmentation


Oct 13, 2021
Libo Wang, Shenghui Fang, Ce Zhang, Rui Li, Chenxi Duan

Figure 1 for Efficient Hybrid Transformer: Learning Global-local Context for Urban Scene Segmentation
Figure 2 for Efficient Hybrid Transformer: Learning Global-local Context for Urban Scene Segmentation
Figure 3 for Efficient Hybrid Transformer: Learning Global-local Context for Urban Scene Segmentation
Figure 4 for Efficient Hybrid Transformer: Learning Global-local Context for Urban Scene Segmentation

  Access Paper or Ask Questions

Towards Automatic Bias Detection in Knowledge Graphs


Sep 19, 2021
Daphna Keidar, Mian Zhong, Ce Zhang, Yash Raj Shrestha, Bibek Paudel

Figure 1 for Towards Automatic Bias Detection in Knowledge Graphs
Figure 2 for Towards Automatic Bias Detection in Knowledge Graphs
Figure 3 for Towards Automatic Bias Detection in Knowledge Graphs
Figure 4 for Towards Automatic Bias Detection in Knowledge Graphs
* Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Findings (EMNLP 2021). Nov 7--11, 2021 
  Access Paper or Ask Questions

Efficient Hybrid Transformer: Learning Global-local Context for Urban Sence Segmentation


Sep 18, 2021
Libo Wang, Shenghui Fang, Ce Zhang, Rui Li, Chenxi Duan

Figure 1 for Efficient Hybrid Transformer: Learning Global-local Context for Urban Sence Segmentation
Figure 2 for Efficient Hybrid Transformer: Learning Global-local Context for Urban Sence Segmentation
Figure 3 for Efficient Hybrid Transformer: Learning Global-local Context for Urban Sence Segmentation
Figure 4 for Efficient Hybrid Transformer: Learning Global-local Context for Urban Sence Segmentation

  Access Paper or Ask Questions

Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee


Aug 30, 2021
Cedric Renggli, Luka Rimanic, Nora Hollenstein, Ce Zhang

Figure 1 for Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee
Figure 2 for Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee
Figure 3 for Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee
Figure 4 for Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee
* arXiv admin note: text overlap with arXiv:2010.08410 
  Access Paper or Ask Questions

LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis


Aug 20, 2021
Fan Wu, Yunhui Long, Ce Zhang, Bo Li

Figure 1 for LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis
Figure 2 for LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis
Figure 3 for LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis
Figure 4 for LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis

  Access Paper or Ask Questions

Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery


Aug 19, 2021
Gyri Reiersen, David Dao, Bj枚rn L眉tjens, Konstantin Klemmer, Xiaoxiang Zhu, Ce Zhang

Figure 1 for Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery
Figure 2 for Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery
Figure 3 for Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery
Figure 4 for Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery
* Spotlight talk at the Tackling Climate Change with Machine Learning workshop at the ICML 2021 https://www.climatechange.ai/papers/icml2021/79 
  Access Paper or Ask Questions

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition


Jul 20, 2021
Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui

Figure 1 for VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition
Figure 2 for VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition
Figure 3 for VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition
Figure 4 for VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition
* 47th International Conference on Very Large Data Bases, VLDB 2021, PVLDB Volume 14, Issue 11 
  Access Paper or Ask Questions

BAGUA: Scaling up Distributed Learning with System Relaxations


Jul 12, 2021
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

Figure 1 for BAGUA: Scaling up Distributed Learning with System Relaxations
Figure 2 for BAGUA: Scaling up Distributed Learning with System Relaxations
Figure 3 for BAGUA: Scaling up Distributed Learning with System Relaxations
Figure 4 for BAGUA: Scaling up Distributed Learning with System Relaxations

  Access Paper or Ask Questions

Attention-based Neural Network for Driving Environment Complexity Perception


Jun 21, 2021
Ce Zhang, Azim Eskandarian, Xuelai Du

Figure 1 for Attention-based Neural Network for Driving Environment Complexity Perception
Figure 2 for Attention-based Neural Network for Driving Environment Complexity Perception
Figure 3 for Attention-based Neural Network for Driving Environment Complexity Perception
Figure 4 for Attention-based Neural Network for Driving Environment Complexity Perception
* Accepted by 2021 IEEE Intelligent Transportation Systems Conference 
  Access Paper or Ask Questions

Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks


Jun 11, 2021
Nezihe Merve G眉rel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li

Figure 1 for Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks
Figure 2 for Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks
Figure 3 for Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks
Figure 4 for Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks
* International Conference on Machine Learning 2021, 37 pages, 8 figures, 9 tables 
  Access Paper or Ask Questions

OpenBox: A Generalized Black-box Optimization Service


Jun 06, 2021
Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui

Figure 1 for OpenBox: A Generalized Black-box Optimization Service
Figure 2 for OpenBox: A Generalized Black-box Optimization Service
Figure 3 for OpenBox: A Generalized Black-box Optimization Service
Figure 4 for OpenBox: A Generalized Black-box Optimization Service
* Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2021) 
  Access Paper or Ask Questions

Towards Demystifying Serverless Machine Learning Training


May 17, 2021
Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang

Figure 1 for Towards Demystifying Serverless Machine Learning Training
Figure 2 for Towards Demystifying Serverless Machine Learning Training
Figure 3 for Towards Demystifying Serverless Machine Learning Training
Figure 4 for Towards Demystifying Serverless Machine Learning Training

  Access Paper or Ask Questions

A Novel Transformer based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images


May 11, 2021
Libo Wang, Rui Li, Chenxi Duan, Ce Zhang, Xiaoliang Meng, Shenghui Fang

Figure 1 for A Novel Transformer based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images
Figure 2 for A Novel Transformer based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images

  Access Paper or Ask Questions

Multilingual Language Models Predict Human Reading Behavior


Apr 12, 2021
Nora Hollenstein, Federico Pirovano, Ce Zhang, Lena J盲ger, Lisa Beinborn

Figure 1 for Multilingual Language Models Predict Human Reading Behavior
Figure 2 for Multilingual Language Models Predict Human Reading Behavior
Figure 3 for Multilingual Language Models Predict Human Reading Behavior
Figure 4 for Multilingual Language Models Predict Human Reading Behavior
* accepted at NAACL 2021 
  Access Paper or Ask Questions

Distributed Learning Systems with First-order Methods


Apr 12, 2021
Ji Liu, Ce Zhang

Figure 1 for Distributed Learning Systems with First-order Methods
Figure 2 for Distributed Learning Systems with First-order Methods
Figure 3 for Distributed Learning Systems with First-order Methods
Figure 4 for Distributed Learning Systems with First-order Methods
* Foundations and Trends in Databases: Vol. 9: No. 1 
  Access Paper or Ask Questions

SaNet: Scale-aware Neural Network for Semantic Labelling of Multiple Spatial Resolution Aerial Images


Apr 10, 2021
Libo Wang, Shenghui Fang, Ce Zhang, Rui Li, Chenxi Duan, Xiaoliang Meng, Peter M. Atkinson

Figure 1 for SaNet: Scale-aware Neural Network for Semantic Labelling of Multiple Spatial Resolution Aerial Images
Figure 2 for SaNet: Scale-aware Neural Network for Semantic Labelling of Multiple Spatial Resolution Aerial Images
Figure 3 for SaNet: Scale-aware Neural Network for Semantic Labelling of Multiple Spatial Resolution Aerial Images
Figure 4 for SaNet: Scale-aware Neural Network for Semantic Labelling of Multiple Spatial Resolution Aerial Images

  Access Paper or Ask Questions

TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness


Apr 01, 2021
Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Benjamin Rubinstein, Ce Zhang, Bo Li

Figure 1 for TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness
Figure 2 for TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness
Figure 3 for TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness
Figure 4 for TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness

  Access Paper or Ask Questions

DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation


Mar 20, 2021
Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li

Figure 1 for DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation
Figure 2 for DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation
Figure 3 for DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation
Figure 4 for DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation
* 29 pages, 3 figures, 6 tables 
  Access Paper or Ask Questions

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting


Mar 13, 2021
Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Conguri Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang

Figure 1 for Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Figure 2 for Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Figure 3 for Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Figure 4 for Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
* Accepted by NeurIPS 2020. 20 pages, 7 figures 
  Access Paper or Ask Questions