Zhenghua Xu : Publications
Journal papers
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[1]
Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation
Yuhang Song‚ Beren Millidge‚ Tommaso Salvatori‚ Thomas Lukasiewicz‚ Zhenghua Xu and Rafal Bogacz
In Nature Neuroscience. 2024.
Details about Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation | BibTeX data for Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation | Link to Inferring Neural Activity Before Plasticity: A Foundation for Learning Beyond Backpropagation
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[2]
Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty
Zhenghua Xu‚ Wenting Xu‚ Ruizhi Wang‚ Junyang Chen‚ Chang Qi and Thomas Lukasiewicz
In IEEE Transactions on Neural Networks and Learning Systems. 2023.
Accepted for publication
Details about Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty | BibTeX data for Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty | Link to Hybrid Reinforced Medical Report Generation with M−Linear Attention and Repetition Penalty
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[3]
Collaborative Attention Guided Multi−Scale Feature Fusion Network for Medical Image Segmentation
Zhenghua Xu‚ Biao Tian‚ Shijie Liu‚ Xiangtao Wang‚ Di Yuan‚ Junhua Gu‚ Junyang Chen‚ Thomas Lukasiewicz and Victor C. M. Leung
In IEEE Transactions on Network Science and Engineering. Vol. 11. No. 2. Pages 1857–1871. 2023.
Details about Collaborative Attention Guided Multi−Scale Feature Fusion Network for Medical Image Segmentation | BibTeX data for Collaborative Attention Guided Multi−Scale Feature Fusion Network for Medical Image Segmentation | Link to Collaborative Attention Guided Multi−Scale Feature Fusion Network for Medical Image Segmentation
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[4]
RIRGAN: An end−to−end lightweight multi−task learning method for brain MRI super−resolution and denoising
Miao Yu‚ Miaomiao Guo‚ Shuai Zhang‚ Yuefu Zhan‚ Mingkang Zhao‚ Thomas Lukasiewicz and Zhenghua Xu
In Computers in Biology and Medicine. Vol. 167. Pages 107632. 2023.
Details about RIRGAN: An end−to−end lightweight multi−task learning method for brain MRI super−resolution and denoising | BibTeX data for RIRGAN: An end−to−end lightweight multi−task learning method for brain MRI super−resolution and denoising | Link to RIRGAN: An end−to−end lightweight multi−task learning method for brain MRI super−resolution and denoising
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[5]
PhaCIA−TCNs: Short−Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention
Zhenghua Xu‚ Zhoutao Yu‚ Hexiang Zhang‚ Junyang Chen‚ Junhua Gu‚ Thomas Lukasiewicz and Victor Leung
In IEEE Transactions on Network Science and Engineering. August, 2023.
Details about PhaCIA−TCNs: Short−Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention | BibTeX data for PhaCIA−TCNs: Short−Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention | Link to PhaCIA−TCNs: Short−Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention
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[6]
EFPN: Effective medical image detection using feature pyramid fusion enhancement
Zhenghua Xu‚ Xudong Zhang‚ Hexiang Zhang‚ Yunxin Liu‚ Yuefu Zhan and Thomas Lukasiewicz
In Computers in Biology and Medicine. Vol. 163. Pages 107149. 2023.
Details about EFPN: Effective medical image detection using feature pyramid fusion enhancement | BibTeX data for EFPN: Effective medical image detection using feature pyramid fusion enhancement | Link to EFPN: Effective medical image detection using feature pyramid fusion enhancement
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[7]
Multi−ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self−Supervised Medical Image Segmentation
Jiaojiao Zhang‚ Shuo Zhang‚ Xiaoqian Shen‚ Thomas Lukasiewicz and Zhenghua Xu
In IEEE Transactions on Medical Imaging. 2023.
Details about Multi−ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self−Supervised Medical Image Segmentation | BibTeX data for Multi−ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self−Supervised Medical Image Segmentation
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[8]
Painless and accurate medical image analysis using deep reinforcement learning with task−oriented homogenized automatic pre−processing
Di Yuan‚ Yunxin Liu‚ Zhenghua Xu‚ Yuefu Zhan‚ Junyang Chen and Thomas Lukasiewicz
In Computers in Biology and Medicine. Vol. 153. Pages 106487. February, 2023.
Details about Painless and accurate medical image analysis using deep reinforcement learning with task−oriented homogenized automatic pre−processing | BibTeX data for Painless and accurate medical image analysis using deep reinforcement learning with task−oriented homogenized automatic pre−processing | Link to Painless and accurate medical image analysis using deep reinforcement learning with task−oriented homogenized automatic pre−processing
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[9]
μ−Net: Medical image segmentation using efficient and effective deep supervision
Di Yuan‚ Zhenghua Xu‚ Biao Tian‚ Hening Wang‚ Yuefu Zhan and Thomas Lukasiewicz
In Computers in Biology and Medicine. Vol. 160. Pages 106963. June, 2023.
Details about μ−Net: Medical image segmentation using efficient and effective deep supervision | BibTeX data for μ−Net: Medical image segmentation using efficient and effective deep supervision | Link to μ−Net: Medical image segmentation using efficient and effective deep supervision
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[10]
PAC−Net: Multi−Pathway FPN with Position Attention Guided Connections and Vertex Distance IoU for 3D Medical Image Detection
Zhenghua Xu‚ Tianrun Li‚ Yunxin Liu‚ Yuefu Zhan‚ Junyang Chen and Thomas Lukasiewicz
In Frontiers in Bioengineering and Biotechnology. Vol. 11. Pages 1049555. February, 2023.
Details about PAC−Net: Multi−Pathway FPN with Position Attention Guided Connections and Vertex Distance IoU for 3D Medical Image Detection | BibTeX data for PAC−Net: Multi−Pathway FPN with Position Attention Guided Connections and Vertex Distance IoU for 3D Medical Image Detection | Link to PAC−Net: Multi−Pathway FPN with Position Attention Guided Connections and Vertex Distance IoU for 3D Medical Image Detection
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[11]
Multi−Modal Contrastive Mutual Learning and Pseudo−Label Re−Learning for Semi−Supervised Medical Image Segmentation
Shuo Zhang‚ Jiaojiao Zhang‚ Biao Tian‚ Thomas Lukasiewicz and Zhenghua Xu
In Medical Image Analysis. Vol. 83. Pages 102656. January, 2023.
Details about Multi−Modal Contrastive Mutual Learning and Pseudo−Label Re−Learning for Semi−Supervised Medical Image Segmentation | BibTeX data for Multi−Modal Contrastive Mutual Learning and Pseudo−Label Re−Learning for Semi−Supervised Medical Image Segmentation | Link to Multi−Modal Contrastive Mutual Learning and Pseudo−Label Re−Learning for Semi−Supervised Medical Image Segmentation
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[12]
Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks
Haozhe Lin‚ Yushun Fan‚ Jia Zhang‚ Bing Bai‚ Zhenghua Xu and Thomas Lukasiewicz
In IEEE Transactions on Services Computing. Vol. 16. No. 1. Pages 642–655. January, 2022.
Details about Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks | BibTeX data for Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks | Link to Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks
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[13]
ω−Net: Dual Supervised Medical Image Segmentation with Multi−Dimensional Self−Attention and Diversely−Connected Multi−Scale Convolution
Zhenghua Xu‚ Shijie Liu‚ Di Yuan‚ Lei Wang‚ Junyang Chen‚ Thomas Lukasiewicz‚ Zhigang Fu and Rui Zhang
In Neurocomputing. Vol. 500. Pages 177−190. August, 2022.
Details about ω−Net: Dual Supervised Medical Image Segmentation with Multi−Dimensional Self−Attention and Diversely−Connected Multi−Scale Convolution | BibTeX data for ω−Net: Dual Supervised Medical Image Segmentation with Multi−Dimensional Self−Attention and Diversely−Connected Multi−Scale Convolution | Link to ω−Net: Dual Supervised Medical Image Segmentation with Multi−Dimensional Self−Attention and Diversely−Connected Multi−Scale Convolution
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[14]
Lightweight Tag−Aware Personalized Recommendation on the Social Web Using Ontological Similarity
Zhenghua Xu‚ Oana Tifrea−Marciuska‚ Thomas Lukasiewicz‚ Maria Vanina Martinez‚ Gerardo I. Simari and Cheng Chen
In IEEE Access. Vol. 6. No. 1. Pages 35590−35610. July, 2018.
Details about Lightweight Tag−Aware Personalized Recommendation on the Social Web Using Ontological Similarity | BibTeX data for Lightweight Tag−Aware Personalized Recommendation on the Social Web Using Ontological Similarity | Link to Lightweight Tag−Aware Personalized Recommendation on the Social Web Using Ontological Similarity
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[15]
Location−Aware Personalized News Recommendation with Deep Semantic Analysis
Cheng Chen‚ Xiangwu Meng‚ Zhenghua Xu and Thomas Lukasiewicz.
In IEEE Access. Vol. 5. Pages 1624–1638. January, 2017.
Details about Location−Aware Personalized News Recommendation with Deep Semantic Analysis | BibTeX data for Location−Aware Personalized News Recommendation with Deep Semantic Analysis | Link to Location−Aware Personalized News Recommendation with Deep Semantic Analysis
Conference papers
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[1]
A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks
Tommaso Salvatori‚ Yuhang Song‚ Yordan Yordanov‚ Beren Millidge‚ Lei Sha‚ Cornelius Emde‚ Zhenghua Xu‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 12th International Conference on Learning Representations‚ ICLR 2024‚ Vienna‚ Austria‚ 7–11 May 2024. May, 2024.
Details about A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks | BibTeX data for A Stable‚ Fast‚ and Fully Automatic Learning Algorithm for Predictive Coding Networks
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[2]
Multi−Head Feature Pyramid Networks for Breast Mass Detection
Hexiang Zhang‚ Zhenghua Xu‚ Dan Yao‚ Shuo Zhang‚ Junyang Chen and Thomas Lukasiewicz
In Proceedings of the IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2023‚ Rhodes Island‚ Greece‚ 4−10 June 2023. IEEE. 2023.
Details about Multi−Head Feature Pyramid Networks for Breast Mass Detection | BibTeX data for Multi−Head Feature Pyramid Networks for Breast Mass Detection
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[3]
MPS−AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self−Supervised Medical Image Segmentation
Xiangtao Wang‚ Ruizhi Wang‚ Tian Biao‚ Jiaojiao Zhang‚ Shuo Zhang‚ Junyang Chen‚ Thomas Lukasiewicz and Zhenghua Xu
In Proceedings of the IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2023‚ Rhodes Island‚ Greece‚ 4−10 June 2023. IEEE. 2023.
Details about MPS−AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self−Supervised Medical Image Segmentation | BibTeX data for MPS−AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self−Supervised Medical Image Segmentation
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[4]
MvCo−DoT: Multi−View Contrastive Domain Transfer Network for Medical Report Generation
Ruizhi Wang‚ Xiangtao Wang‚ Zhenghua Xu‚ Wenting Xu‚ Junyang Chen and Thomas Lukasiewicz
In Proceedings of the IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2023‚ Rhodes Island‚ Greece‚ 4−10 June 2023. IEEE. 2023.
Details about MvCo−DoT: Multi−View Contrastive Domain Transfer Network for Medical Report Generation | BibTeX data for MvCo−DoT: Multi−View Contrastive Domain Transfer Network for Medical Report Generation
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[5]
Adaptive−Masking Policy with Deep Reinforcement Learning for Self−Supervised Medical Image Segmentation
Gang Xu‚ Shengxin Wang‚ Thomas Lukasiewicz and Zhenghua Xu
In Proceedings of the IEEE International Conference on Multimedia and Expo‚ ICME 2023‚ Brisbane‚ Australia‚ July 10−14‚ 2023. IEEE. 2023.
Details about Adaptive−Masking Policy with Deep Reinforcement Learning for Self−Supervised Medical Image Segmentation | BibTeX data for Adaptive−Masking Policy with Deep Reinforcement Learning for Self−Supervised Medical Image Segmentation
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[6]
Reverse Differentiation via Predictive Coding
Tommaso Salvatori‚ Yuhang Song‚ Zhenghua Xu‚ Thomas Lukasiewicz and Rafal Bogacz
In Proceedings of the 36th AAAI Conference on Artificial Intelligence‚ AAAI 2022‚ Vancouver‚ BC‚ Canada‚ February 22 – March 1‚ 2022. Pages 8150–8158. AAAI Press. February, 2022.
Details about Reverse Differentiation via Predictive Coding | BibTeX data for Reverse Differentiation via Predictive Coding | Link to Reverse Differentiation via Predictive Coding
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[7]
Associative Memories via Predictive Coding
Tommaso Salvatori‚ Yuhang Song‚ Yujian Hong‚ Simon Frieder‚ Lei Sha‚ Zhenghua Xu‚ Rafal Bogacz and Thomas Lukasiewicz
In Proceedings of the 35th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2021. December, 2021.
Details about Associative Memories via Predictive Coding | BibTeX data for Associative Memories via Predictive Coding | Link to Associative Memories via Predictive Coding
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[8]
RSG: A Simple yet Effective Module for Learning Imbalanced Datasets
Jianfeng Wang‚ Thomas Lukasiewicz‚ Xiaolin Hu‚ Jianfei Cai and Zhenghua Xu
In Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition‚ CVPR 2021‚ Virtual‚ June 19–25‚ 2021. June, 2021.
Details about RSG: A Simple yet Effective Module for Learning Imbalanced Datasets | BibTeX data for RSG: A Simple yet Effective Module for Learning Imbalanced Datasets | Link to RSG: A Simple yet Effective Module for Learning Imbalanced Datasets
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[9]
Can the Brain Do Backpropagation? — Exact Implementation of Backpropagation in Predictive Coding Networks
Yuhang Song‚ Thomas Lukasiewicz‚ Zhenghua Xu and Rafal Bogacz
In Proceedings of the 34th Annual Conference on Neural Information Processing Systems‚ NeurIPS 2020‚ December 6–12‚ 2020. December, 2020.
Details about Can the Brain Do Backpropagation? — Exact Implementation of Backpropagation in Predictive Coding Networks | BibTeX data for Can the Brain Do Backpropagation? — Exact Implementation of Backpropagation in Predictive Coding Networks | Link to Can the Brain Do Backpropagation? — Exact Implementation of Backpropagation in Predictive Coding Networks
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[10]
Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation
Zhenghua Xu‚ Di Yuan‚ Thomas Lukasiewicz‚ Cheng Chen‚ Yishu Miao and Guizhi Xu
In Proceedings of the 2020 IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2020‚ Barcelona‚ Spain‚ May 4–8‚ 2020. IEEE Computer Society. May, 2020.
Details about Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation | BibTeX data for Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation | Link to Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation
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[11]
Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence
Yuhang Song‚ Andrzej Wojcicki‚ Thomas Lukasiewicz‚ Jianyi Wang‚ Abi Aryan‚ Zhenghua Xu‚ Mai Xu‚ Zihan Ding and Lianlong Wu
In Vincent Conitzer and Fei Sha, editors, Proceedings of the 34th National Conference on Artificial Intelligence‚ AAAI 2020‚ New York‚ New York‚ USA‚ February 7–12‚ 2020. AAAI Press. February, 2020.
Details about Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence | BibTeX data for Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence | Link to Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence
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[12]
Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards
Yuhang Song‚ Jianyi Wang‚ Thomas Lukasiewicz‚ Zhenghua Xu‚ Shangtong Zhang‚ Andrzej Wojcicki and Mai Xu
In Vincent Conitzer and Fei Sha, editors, Proceedings of the 34th National Conference on Artificial Intelligence‚ AAAI 2020‚ New York‚ New York‚ USA‚ February 7–12‚ 2020. AAAI Press. February, 2020.
Details about Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards | BibTeX data for Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards | Link to Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards
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[13]
Long Text Analysis Using Sliced Recurrent Neural Networks with Breaking Point Information Enrichment
Bo Li‚ Zehua Cheng‚ Zhenghua Xu‚ Wei Ye‚ Thomas Lukasiewicz and Shikun Zhang
In Proceedings of the 2019 IEEE International Conference on Acoustics‚ Speech and Signal Processing‚ ICASSP 2019‚ Brighton‚ UK‚ May 12−17‚ 2019. IEEE Computer Society. May, 2019.
Details about Long Text Analysis Using Sliced Recurrent Neural Networks with Breaking Point Information Enrichment | BibTeX data for Long Text Analysis Using Sliced Recurrent Neural Networks with Breaking Point Information Enrichment | Link to Long Text Analysis Using Sliced Recurrent Neural Networks with Breaking Point Information Enrichment
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[14]
Diversity−Driven Extensible Hierarchical Reinforcement Learning
Yuhang Song‚ Jianyi Wang‚ Thomas Lukasiewicz‚ Zhenghua Xu and Mai Xu
In Pascal Van Hentenryck and Zhi−Hua Zhou, editors, Proceedings of the 33rd National Conference on Artificial Intelligence‚ AAAI 2019‚ Honolulu‚ Hawaii‚ USA‚ January 27 − February 1‚ 2019. Pages 4992–4999. AAAI Press. January, 2019.
Details about Diversity−Driven Extensible Hierarchical Reinforcement Learning | BibTeX data for Diversity−Driven Extensible Hierarchical Reinforcement Learning | Link to Diversity−Driven Extensible Hierarchical Reinforcement Learning
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[15]
Tag−Aware Personalized Recommendation Using a Hybrid Deep Model
Zhenghua Xu‚ Thomas Lukasiewicz‚ Cheng Chen‚ Yishu Miao and Xiangwu Meng
In Carles Sierra, editor, Proceedings of the 26th International Joint Conference on Artificial Intelligence‚ IJCAI 2017‚ Melbourne‚ Australia‚ August 19−25‚ 2017. Pages 3196–3202. IJCAI/AAAI Press. August, 2017.
Details about Tag−Aware Personalized Recommendation Using a Hybrid Deep Model | BibTeX data for Tag−Aware Personalized Recommendation Using a Hybrid Deep Model | Download (pdf) of Tag−Aware Personalized Recommendation Using a Hybrid Deep Model
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[16]
Location−Aware News Recommendation Using Deep Localized Semantic Analysis
Cheng Chen‚ Thomas Lukasiewicz‚ Xiangwu Meng and Zhenghua Xu
In Selçuk Candan‚ Lei Chen and Torben Bach Pedersen, editors, Proceedings of the 22nd International Conference on Database Systems for Advanced Applications‚ DASFAA 2017‚ Suzhou‚ China‚ March 27−30‚ 2017. Vol. 10177 of Lecture Notes in Computer Science. Pages 507–524. Springer. 2017.
Details about Location−Aware News Recommendation Using Deep Localized Semantic Analysis | BibTeX data for Location−Aware News Recommendation Using Deep Localized Semantic Analysis | Link to Location−Aware News Recommendation Using Deep Localized Semantic Analysis
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[17]
Tag−Aware Personalized Recommendation Using a Deep−Semantic Similarity Model with Negative Sampling
Zhenghua Xu‚ Cheng Chen‚ Thomas Lukasiewicz‚ Yishu Miao and Xiangwu Meng
In Elisa Bertino‚ Fabio Crestani‚ Javed Mostafa‚ Jie Tang‚ Luo Si and Xiaofang Zhou, editors, Proceedings of the 25th ACM International Conference on Information and Knowledge Management‚ CIKM 2016‚ Indianapolis‚ USA‚ October 24−28‚ 2016. Pages 1921−1924. ACM Press. October, 2016.
Details about Tag−Aware Personalized Recommendation Using a Deep−Semantic Similarity Model with Negative Sampling | BibTeX data for Tag−Aware Personalized Recommendation Using a Deep−Semantic Similarity Model with Negative Sampling | Link to Tag−Aware Personalized Recommendation Using a Deep−Semantic Similarity Model with Negative Sampling
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[18]
Improving Personalized Search on the Social Web Based on Similarities Between Users
Zhenghua Xu‚ Thomas Lukasiewicz and Oana Tifrea−Marciuska
In Umberto Straccia and Andrea Calì, editors, Proceedings of the 8th International Conference on Scalable Uncertainty Management‚ SUM 2014‚ Oxford‚ UK‚ September 15−17‚ 2014. Vol. 8720 of Lecture Notes in Computer Science. Pages 306−319. Springer. 2014.
Details about Improving Personalized Search on the Social Web Based on Similarities Between Users | BibTeX data for Improving Personalized Search on the Social Web Based on Similarities Between Users | Link to Improving Personalized Search on the Social Web Based on Similarities Between Users
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[19]
Destination prediction by sub−trajectory synthesis and privacy protection against such prediction
Andy Yuan Xue‚ Rui Zhang‚ Yu Zheng‚ Xing Xie‚ Jin Huang and Zhenghua Xu
In Christian S. Jensen‚ Christopher M. Jermaine and Xiaofang Zhou, editors, 29th IEEE International Conference on Data Engineering‚ ICDE 2013‚ Brisbane‚ Australia‚ April 8−12‚ 2013. Pages 254−265. IEEE Computer Society. 2013.
Details about Destination prediction by sub−trajectory synthesis and privacy protection against such prediction | BibTeX data for Destination prediction by sub−trajectory synthesis and privacy protection against such prediction | Link to Destination prediction by sub−trajectory synthesis and privacy protection against such prediction
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[20]
An adaptive algorithm for online time series segmentation with error bound guarantee
Zhenghua Xu‚ Rui Zhang‚ Kotagiri Ramamohanarao and Udaya Parampalli
In Elke A. Rundensteiner‚ Volker Markl‚ Ioana Manolescu‚ Sihem Amer−Yahia‚ Felix Naumann and Ismail Ari, editors, 15th International Conference on Extending Database Technology‚ EDBT '12‚ Berlin‚ Germany‚ March 27−30‚ 2012‚ Proceedings. Pages 192−203. ACM. 2012.
Details about An adaptive algorithm for online time series segmentation with error bound guarantee | BibTeX data for An adaptive algorithm for online time series segmentation with error bound guarantee | Link to An adaptive algorithm for online time series segmentation with error bound guarantee
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[21]
A Branch and Bound Method for Min−dist Location Selection Queries
Jianzhong Qi‚ Zhenghua Xu‚ Yuan Xue and Zeyi Wen
In Rui Zhang and Yanchun Zhang, editors, Twenty−Third Australasian Database Conference‚ ADC 2012‚ Melbourne‚ Australia‚ January 2012. Vol. 124 of CRPIT. Pages 51−60. Australian Computer Society. 2012.
Details about A Branch and Bound Method for Min−dist Location Selection Queries | BibTeX data for A Branch and Bound Method for Min−dist Location Selection Queries
Technical reports
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[1]
Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation
Zhenghua Xu‚ Cheng Chen‚ Thomas Lukasiewicz and Yishu Miao
2017.
Details about Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation | BibTeX data for Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation | Link to Hybrid Deep−Semantic Matrix Factorization for Tag−Aware Personalized Recommendation