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2020 – today
- 2024
[j8]Yifan He
, Yatao Bian, Xi Ding, Bingzhe Wu, Jihong Guan, Ji Zhang, Shuigeng Zhou:
Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection. ACM Trans. Knowl. Discov. Data 18(8): 187:1-187:24 (2024)- [c36]Fan Xu, Yu Zhao, Bingzhe Wu, Yueshan Huang, Qin Ren, Yang Xiao, Bing He, Jie Zheng, Jianhua Yao:
A Label Disambiguation-Based Multimodal Massive Multiple Instance Learning Approach for Immune Repertoire Classification. AAAI 2024: 16138-16146 - [c35]Zihao Zhu, Mingda Zhang, Shaokui Wei, Bingzhe Wu, Baoyuan Wu:
VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models. ICLR 2024 - [c34]Ziqi Gao, Qichao Wang, Aochuan Chen, Zijing Liu, Bingzhe Wu, Liang Chen, Jia Li:
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform. ICML 2024 - [c33]Yan Zhu, Huan Ma, Changqing Zhang, Bingzhe Wu, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu:
Rethinking the Reliability of Post-hoc Calibration Methods Under Subpopulation Shift. PRICAI (2) 2024: 16-28 - [c32]Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
Rethinking and Simplifying Bootstrapped Graph Latents. WSDM 2024: 665-673 - [i53]Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao:
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. CoRR abs/2402.07610 (2024) - [i52]Zhihang Yuan, Yuzhang Shang, Yang Zhou, Zhen Dong, Zhe Zhou, Chenhao Xue, Bingzhe Wu, Zhikai Li, Qingyi Gu, Yong Jae Lee, Yan Yan, Beidi Chen, Guangyu Sun, Kurt Keutzer:
LLM Inference Unveiled: Survey and Roofline Model Insights. CoRR abs/2402.16363 (2024) - [i51]Huan Ma, Yan Zhu, Changqing Zhang, Peilin Zhao, Baoyuan Wu, Long-Kai Huang, Qinghua Hu, Bingzhe Wu:
Invariant Test-Time Adaptation for Vision-Language Model Generalization. CoRR abs/2403.00376 (2024) - [i50]Ziqi Gao, Qichao Wang, Aochuan Chen, Zijing Liu, Bingzhe Wu, Liang Chen, Jia Li:
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform. CoRR abs/2405.03003 (2024) - [i49]Zihao Zhu, Bingzhe Wu, Zhengyou Zhang, Baoyuan Wu:
RiskAwareBench: Towards Evaluating Physical Risk Awareness for High-level Planning of LLM-based Embodied Agents. CoRR abs/2408.04449 (2024) - [i48]Haoyu Wang, Bingzhe Wu, Yatao Bian, Yongzhe Chang, Xueqian Wang, Peilin Zhao:
Probing the Safety Response Boundary of Large Language Models via Unsafe Decoding Path Generation. CoRR abs/2408.10668 (2024) - 2023
- [j7]Qiankun Wang, Xingchen Li, Bingzhe Wu, Ke Yang, Wei Hu, Guangyu Sun, Yuchao Yang:
COPPER: a combinatorial optimization problem solver with processing-in-memory architecture. Frontiers Inf. Technol. Electron. Eng. 24(5): 731-741 (2023) - [j6]Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao:
Dynamics Adapted Imitation Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j5]Zhaoyang Han, Chunpeng Ge, Bingzhe Wu, Zhe Liu:
Lightweight Privacy-Preserving Federated Incremental Decision Trees. IEEE Trans. Serv. Comput. 16(3): 1964-1975 (2023) - [c31]Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian:
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations. AAAI 2023: 8023-8031 - [c30]Zhen Zhang, Mengting Hu, Shiwan Zhao, Minlie Huang, Haotian Wang, Lemao Liu, Zhirui Zhang, Zhe Liu, Bingzhe Wu:
E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition. ACL (Findings) 2023: 1619-1634 - [c29]Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Changqing Zhang, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Bingzhe Wu, Liang Chen:
Attention Paper: How Generative AI Reshapes Digital Shadow Industry? ACM TUR-C 2023: 143-144 - [c28]Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM 2023: 1389-1399 - [c27]Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan:
Post-Training Quantization on Diffusion Models. CVPR 2023: 1972-1981 - [c26]Jianfeng Wu, Mengting Hu, Yike Wu, Bingzhe Wu, Yalan Xie, Mingming Liu, Renhong Cheng:
Density-Aware Prototypical Network for Few-Shot Relation Classification. EMNLP (Findings) 2023: 2477-2489 - [c25]Tao Yang, Tianyuan Shi, Fanqi Wan, Xiaojun Quan, Qifan Wang, Bingzhe Wu, Jiaxiang Wu:
PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection. EMNLP (Findings) 2023: 3305-3320 - [c24]Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong:
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. EMNLP 2023: 6325-6341 - [c23]Haotian Wang, Zhen Zhang, Mengting Hu, Qichao Wang, Liang Chen, Yatao Bian, Bingzhe Wu:
RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data. EMNLP (Findings) 2023: 7246-7257 - [c22]Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng:
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR 2023 - [c21]Yichao Du, Zhirui Zhang, Bingzhe Wu, Lemao Liu, Tong Xu, Enhong Chen:
Federated Nearest Neighbor Machine Translation. ICLR 2023 - [c20]Huan Ma, Qingyang Zhang, Changqing Zhang, Bingzhe Wu, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu:
Calibrating Multimodal Learning. ICML 2023: 23429-23450 - [c19]Zeyu Cao, Zhipeng Liang, Bingzhe Wu, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao:
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation. KDD 2023: 154-166 - [c18]Qin Ren, Yu Zhao, Bing He, Bingzhe Wu, Sijie Mai, Fan Xu, Yueshan Huang, Yonghong He, Junzhou Huang, Jianhua Yao:
IIB-MIL: Integrated Instance-Level and Bag-Level Multiple Instances Learning with Label Disambiguation for Pathological Image Analysis. MICCAI (6) 2023: 560-569 - [c17]Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu:
Fairness-guided Few-shot Prompting for Large Language Models. NeurIPS 2023 - [i47]Yichao Du, Zhirui Zhang, Bingzhe Wu, Lemao Liu, Tong Xu, Enhong Chen:
Federated Nearest Neighbor Machine Translation. CoRR abs/2302.12211 (2023) - [i46]Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu:
Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance. CoRR abs/2303.13003 (2023) - [i45]Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang, Peilin Zhao, Shu Zhang, Huazhu Fu, Qinghua Hu, Bingzhe Wu:
Fairness-guided Few-shot Prompting for Large Language Models. CoRR abs/2303.13217 (2023) - [i44]Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu:
RPTQ: Reorder-based Post-training Quantization for Large Language Models. CoRR abs/2304.01089 (2023) - [i43]Tianchen Zhou, Zhanyi Hu, Bingzhe Wu, Cen Chen:
SLPerf: a Unified Framework for Benchmarking Split Learning. CoRR abs/2304.01502 (2023) - [i42]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Qinghua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
Reweighted Mixup for Subpopulation Shift. CoRR abs/2304.04148 (2023) - [i41]Zhen Zhang, Mengting Hu, Shiwan Zhao, Minlie Huang, Haotian Wang, Lemao Liu, Zhirui Zhang, Zhe Liu, Bingzhe Wu:
E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition. CoRR abs/2305.17854 (2023) - [i40]Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Liang Chen, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Zibin Zheng, Bingzhe Wu:
Attention Paper: How Generative AI Reshapes Digital Shadow Industry? CoRR abs/2305.18346 (2023) - [i39]Huan Ma, Qingyang Zhang, Changqing Zhang, Bingzhe Wu, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu:
Calibrating Multimodal Learning. CoRR abs/2306.01265 (2023) - [i38]Mengting Hu, Zhen Zhang, Shiwan Zhao, Minlie Huang, Bingzhe Wu:
Uncertainty in Natural Language Processing: Sources, Quantification, and Applications. CoRR abs/2306.04459 (2023) - [i37]Zongbo Han, Tianchi Xie, Bingzhe Wu, Qinghua Hu, Changqing Zhang:
Semantic Equivariant Mixup. CoRR abs/2308.06451 (2023) - [i36]Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CoRR abs/2308.06801 (2023) - [i35]Bingzhe Wu:
Is GPT4 a Good Trader? CoRR abs/2309.10982 (2023) - [i34]Zihao Zhu, Mingda Zhang, Shaokui Wei, Bingzhe Wu, Baoyuan Wu:
VDC: Versatile Data Cleanser for Detecting Dirty Samples via Visual-Linguistic Inconsistency. CoRR abs/2309.16211 (2023) - [i33]Huan Ma, Changqing Zhang, Huazhu Fu, Peilin Zhao, Bingzhe Wu:
Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning. CoRR abs/2310.03400 (2023) - [i32]Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong:
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. CoRR abs/2310.07289 (2023) - [i31]Qichao Wang, Tian Bian, Yian Yin, Tingyang Xu, Hong Cheng, Helen M. Meng, Zibin Zheng, Liang Chen, Bingzhe Wu:
Language Agents for Detecting Implicit Stereotypes in Text-to-image Models at Scale. CoRR abs/2310.11778 (2023) - [i30]Tao Yang, Tianyuan Shi, Fanqi Wan, Xiaojun Quan, Qifan Wang, Bingzhe Wu, Jiaxiang Wu:
PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection. CoRR abs/2310.20256 (2023) - [i29]Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-Fai Wong:
X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. CoRR abs/2311.09832 (2023) - [i28]Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
Rethinking and Simplifying Bootstrapped Graph Latents. CoRR abs/2312.02619 (2023) - 2022
- [j4]Jun Zhou, Longfei Zheng, Chaochao Chen, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin:
Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. ACM Trans. Intell. Syst. Technol. 13(4): 53:1-53:21 (2022) - [c16]Xingchen Li, Bingzhe Wu, Guangyu Sun, Zhe Zhang, Zhihang Yuan, Runsheng Wang, Ru Huang, Dimin Niu, Hongzhong Zheng, Zhichao Lu, Liang Zhao, Meng-Fan Marvin Chang, Tianchan Guan, Xin Si:
Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network. HPCA 2022: 1043-1055 - [c15]Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng:
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification. IJCAI 2022: 1959-1965 - [c14]Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang:
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. KDD 2022: 4838-4839 - [c13]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. NeurIPS 2022 - [i27]Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Long-Kai Huang, Tingyang Xu, Yu Rong, Lanqing Li, Jie Ren, Ding Xue, Houtim Lai, Shaoyong Xu, Jing Feng, Wei Liu, Ping Luo, Shuigeng Zhou, Junzhou Huang, Peilin Zhao, Yatao Bian:
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations. CoRR abs/2201.09637 (2022) - [i26]Bingzhe Wu, Jintang Li, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen, Junzhou Huang:
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift. CoRR abs/2202.07114 (2022) - [i25]Bingzhe Wu, Zhipeng Liang, Yuxuan Han, Yatao Bian, Peilin Zhao, Junzhou Huang:
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup. CoRR abs/2204.07742 (2022) - [i24]Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, Chaochao Chen, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao:
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR abs/2205.10014 (2022) - [i23]Lanqing Li, Liang Zeng, Ziqi Gao, Shen Yuan, Yatao Bian, Bingzhe Wu, Hengtong Zhang, Chan Lu, Yang Yu, Wei Liu, Hongteng Xu, Jia Li, Peilin Zhao, Pheng-Ann Heng:
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. CoRR abs/2209.07921 (2022) - [i22]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. CoRR abs/2209.08928 (2022) - [i21]Zeyu Cao, Zhipeng Liang, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao, Bingzhe Wu:
Vertical Federated Linear Contextual Bandits. CoRR abs/2210.11050 (2022) - [i20]Mingcai Chen, Yu Zhao, Bing He, Zongbo Han, Bingzhe Wu, Jianhua Yao:
Learning with Noisy Labels over Imbalanced Subpopulations. CoRR abs/2211.08722 (2022) - [i19]Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan:
Post-training Quantization on Diffusion Models. CoRR abs/2211.15736 (2022) - 2021
- [j3]Zhihang Yuan, Jingze Liu, Xingchen Li, Longhao Yan, Haoxiang Chen, Bingzhe Wu, Yuchao Yang, Guangyu Sun:
NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators. Sci. China Inf. Sci. 64(6) (2021) - [j2]Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang:
ASFGNN: Automated separated-federated graph neural network. Peer-to-Peer Netw. Appl. 14(3): 1692-1704 (2021) - [c12]Qingcheng Xiao, Size Zheng, Bingzhe Wu, Pengcheng Xu, Xuehai Qian, Yun Liang:
HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation. ISCA 2021: 1055-1068 - [i18]Qingcheng Xiao, Size Zheng, Bingzhe Wu, Pengcheng Xu, Xuehai Qian, Yun Liang:
HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation. CoRR abs/2105.01585 (2021) - [i17]Bingzhe Wu, Zhicong Liang, Yatao Bian, Chaochao Chen, Junzhou Huang, Yuan Yao:
Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis. CoRR abs/2112.08439 (2021) - 2020
- [j1]Chaochao Chen, Jun Zhou, Bingzhe Wu, Wenjing Fang, Li Wang, Yuan Qi, Xiaolin Zheng:
Practical Privacy Preserving POI Recommendation. ACM Trans. Intell. Syst. Technol. 11(5): 52:1-52:20 (2020) - [c11]Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou:
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. AAAI 2020: 6372-6379 - [c10]Cen Chen, Bingzhe Wu, Li Wang, Chaochao Chen, Jin Tan, Lei Wang, Jun Zhou, Benyu Zhang:
Nebula: A Scalable Privacy-Preserving Machine Learning System in Ant Financial. CIKM 2020: 3369-3372 - [c9]Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou:
Secure Social Recommendation Based on Secret Sharing. ECAI 2020: 506-512 - [c8]Zhihang Yuan, Bingzhe Wu, Guangyu Sun, Zheng Liang, Shiwan Zhao, Weichen Bi:
S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search. ECCV (2) 2020: 175-192 - [c7]Zhe Zhou, Bingzhe Wu, Zheng Liang, Guangyu Sun, Chenren Xu, Guojie Luo:
SaFace: Towards Scenario-aware Face Recognition via Edge Computing System. HotEdge 2020 - [c6]Cen Chen, Ya-Lin Zhang, Minghui Qiu, Bingzhe Wu, Li Wang, Longfei Li, Jun Zhou:
Automatic Knowledge Fusion in Transferrable Networks for Semantic Text Matching. WWW (Companion Volume) 2020: 73-74 - [i16]Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou:
Secure Social Recommendation based on Secret Sharing. CoRR abs/2002.02088 (2020) - [i15]Chaochao Chen, Bingzhe Wu, Wenjin Fang, Jun Zhou, Li Wang, Yuan Qi, Xiaolin Zheng:
Practical Privacy Preserving POI Recommendation. CoRR abs/2003.02834 (2020) - [i14]Longfei Zheng, Chaochao Chen, Yingting Liu, Bingzhe Wu, Xibin Wu, Li Wang, Lei Wang, Jun Zhou, Shuang Yang:
Industrial Scale Privacy Preserving Deep Neural Network. CoRR abs/2003.05198 (2020) - [i13]Jun Zhou, Chaochao Chen, Longfei Zheng, Xiaolin Zheng, Bingzhe Wu, Ziqi Liu, Li Wang:
Privacy-Preserving Graph Neural Network for Node Classification. CoRR abs/2005.11903 (2020) - [i12]Cen Chen, Bingzhe Wu, Minghui Qiu, Li Wang, Jun Zhou:
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning. CoRR abs/2009.01989 (2020) - [i11]Zhihang Yuan, Xin Liu, Bingzhe Wu, Guangyu Sun:
ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference. CoRR abs/2009.09182 (2020) - [i10]Junming Ma, Chaofan Yu, Aihui Zhou, Bingzhe Wu, Xibin Wu, Xingyu Chen, Xiangqun Chen, Lei Wang, Donggang Cao:
S3ML: A Secure Serving System for Machine Learning Inference. CoRR abs/2010.06212 (2020) - [i9]Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang:
ASFGNN: Automated Separated-Federated Graph Neural Network. CoRR abs/2011.03248 (2020) - [i8]Chaochao Chen, Jun Zhou, Longfei Zheng, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin:
Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. CoRR abs/2012.09364 (2020)
2010 – 2019
- 2019
- [c5]Bingzhe Wu, Xiaolu Zhang, Shiwan Zhao, Lingxi Xie, Caihong Zeng, Zhihong Liu, Guangyu Sun:
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification. AAAI 2019: 1214-1221 - [c4]Bingzhe Wu, Shiwan Zhao, Guangyu Sun, Xiaolu Zhang, Zhong Su, Caihong Zeng, Zhihong Liu:
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification. CVPR 2019: 2099-2108 - [c3]Peichen Xie, Bingzhe Wu, Guangyu Sun:
BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference. IJCAI 2019: 4831-4837 - [c2]Bingzhe Wu, Shiwan Zhao, Chaochao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou:
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection. NeurIPS 2019: 306-316 - [i7]Bingzhe Wu, Shiwan Zhao, Guangyu Sun, Xiaolu Zhang, Zhong Su, Caihong Zeng, Zhihong Liu:
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification. CoRR abs/1905.12883 (2019) - [i6]Peichen Xie, Bingzhe Wu, Guangyu Sun:
BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference. CoRR abs/1906.00639 (2019) - [i5]Bingzhe Wu, Shiwan Zhao, Haoyang Xu, Chaochao Chen, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou:
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection. CoRR abs/1908.07882 (2019) - [i4]Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou:
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. CoRR abs/1910.02249 (2019) - [i3]Zhihang Yuan, Bingzhe Wu, Zheng Liang, Shiwan Zhao, Weichen Bi, Guangyu Sun:
S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search. CoRR abs/1911.07033 (2019) - 2018
- [i2]Bingzhe Wu, Xiaolu Zhang, Shiwan Zhao, Lingxi Xie, Caihong Zeng, Zhihong Liu, Guangyu Sun:
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification. CoRR abs/1807.03136 (2018) - 2017
- [c1]Bingzhe Wu, Zhichao Liu, Zhihang Yuan, Guangyu Sun, Charles Wu:
Reducing Overfitting in Deep Convolutional Neural Networks Using Redundancy Regularizer. ICANN (2) 2017: 49-55 - [i1]Bingzhe Wu, Haodong Duan, Zhichao Liu, Guangyu Sun:
SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution. CoRR abs/1712.05927 (2017)
Coauthor Index