Bingzhe Wu

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 92

Top Topics

Privacy Preserving

Stochastic Gradient

Top Venues

EMNLP (Findings)

Publications

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 (2024)
Ziqi Gao, Qichao Wang, Aochuan Chen, Zijing Liu, Bingzhe Wu, Liang Chen, Jia Li
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform. CoRR (2024)
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)
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 (2024)
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 (2024)
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)
Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
Rethinking and Simplifying Bootstrapped Graph Latents. WSDM (2024)
Bingzhe Wu
Is GPT4 a Good Trader? CoRR (2023)
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 (2023)
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)
Zongbo Han, Tianchi Xie, Bingzhe Wu, Qinghua Hu, Changqing Zhang
Semantic Equivariant Mixup. CoRR (2023)
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)
Mengting Hu, Zhen Zhang, Shiwan Zhao, Minlie Huang, Bingzhe Wu
Uncertainty in Natural Language Processing: Sources, Quantification, and Applications. CoRR (2023)
Huan Ma, Qingyang Zhang, Changqing Zhang, Bingzhe Wu, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu
Calibrating Multimodal Learning. ICML (2023)
Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CoRR (2023)
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 (2023)
Tianchen Zhou, Zhanyi Hu, Bingzhe Wu, Cen Chen
SLPerf: a Unified Framework for Benchmarking Split Learning. CoRR (2023)
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 (2023)
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 (2023)
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 (2023)
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)
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) (2023)
Yichao Du, Zhirui Zhang, Bingzhe Wu, Lemao Liu, Tong Xu, Enhong Chen
Federated Nearest Neighbor Machine Translation. ICLR (2023)
Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
Rethinking and Simplifying Bootstrapped Graph Latents. CoRR (2023)
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 (2023)
Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan
Post-Training Quantization on Diffusion Models. CVPR (2023)
Zhaoyang Han, Chunpeng Ge, Bingzhe Wu, Zhe Liu
Lightweight Privacy-Preserving Federated Incremental Decision Trees. IEEE Trans. Serv. Comput. 16 (3) (2023)
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)
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)
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 (2023)
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)
Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-Fai Wong
X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. CoRR (2023)
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)
Yichao Du, Zhirui Zhang, Bingzhe Wu, Lemao Liu, Tong Xu, Enhong Chen
Federated Nearest Neighbor Machine Translation. CoRR (2023)
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 (2023)
Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao
Dynamics Adapted Imitation Learning. Trans. Mach. Learn. Res. 2023 (2023)
Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM (2023)
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)
Zihao Zhu, Mingda Zhang, Shaokui Wei, Bingzhe Wu, Baoyuan Wu
VDC: Versatile Data Cleanser for Detecting Dirty Samples via Visual-Linguistic Inconsistency. CoRR (2023)
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)
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 (2023)
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)
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 (2023)
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)
Huan Ma, Qingyang Zhang, Changqing Zhang, Bingzhe Wu, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu
Calibrating Multimodal Learning. CoRR (2023)
Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan
Post-training Quantization on Diffusion Models. CoRR (2022)
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 (2022)
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)
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 (2022)
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 (2022)
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)
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)
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 (2022)
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)
Zeyu Cao, Zhipeng Liang, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao, Bingzhe Wu
Vertical Federated Linear Contextual Bandits. CoRR (2022)
Mingcai Chen, Yu Zhao, Bing He, Zongbo Han, Bingzhe Wu, Jianhua Yao
Learning with Noisy Labels over Imbalanced Subpopulations. CoRR (2022)
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) (2022)
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 (2022)
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 (2022)
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) (2021)
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)
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 (2021)
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)
Qingcheng Xiao, Size Zheng, Bingzhe Wu, Pengcheng Xu, Xuehai Qian, Yun Liang
HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation. CoRR (2021)
Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou
Secure Social Recommendation Based on Secret Sharing. ECAI (2020)
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)
Cen Chen, Bingzhe Wu, Minghui Qiu, Li Wang, Jun Zhou
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning. CoRR (2020)
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) (2020)
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)
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)
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 (2020)
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)
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 (2020)
Jun Zhou, Chaochao Chen, Longfei Zheng, Xiaolin Zheng, Bingzhe Wu, Ziqi Liu, Li Wang
Privacy-Preserving Graph Neural Network for Node Classification. CoRR (2020)
Zhihang Yuan, Xin Liu, Bingzhe Wu, Guangyu Sun
ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference. CoRR (2020)
Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou
Secure Social Recommendation based on Secret Sharing. CoRR (2020)
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 (2020)
Zhe Zhou, Bingzhe Wu, Zheng Liang, Guangyu Sun, Chenren Xu, Guojie Luo
SaFace: Towards Scenario-aware Face Recognition via Edge Computing System. HotEdge (2020)
Chaochao Chen, Bingzhe Wu, Wenjin Fang, Jun Zhou, Li Wang, Yuan Qi, Xiaolin Zheng
Practical Privacy Preserving POI Recommendation. CoRR (2020)
Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang
ASFGNN: Automated Separated-Federated Graph Neural Network. CoRR (2020)
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 (2019)
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 (2019)
Peichen Xie, Bingzhe Wu, Guangyu Sun
BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference. CoRR (2019)
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 (2019)
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)
Peichen Xie, Bingzhe Wu, Guangyu Sun
BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference. IJCAI (2019)
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)
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)
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 (2019)
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 (2018)
Bingzhe Wu, Haodong Duan, Zhichao Liu, Guangyu Sun
SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution. CoRR (2017)
Bingzhe Wu, Zhichao Liu, Zhihang Yuan, Guangyu Sun, Charles Wu
Reducing Overfitting in Deep Convolutional Neural Networks Using Redundancy Regularizer. ICANN (2) (2017)