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Huifeng Guo
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2020 – today
- 2024
- [j12]Shiwei Li
, Huifeng Guo
Embedding Compression in Recommender Systems: A Survey. ACM Comput. Surv. 56(5): 130:1-130:21 (2024) - [j11]Ziru Liu
AutoAssign+: Automatic Shared Embedding Assignment in streaming recommendation. Knowl. Inf. Syst. 66(1): 89-113 (2024) - [j10]Zehui Mao
Graph Convolutional Neural Network for Intelligent Fault Diagnosis of Machines via Knowledge Graph. IEEE Trans. Ind. Informatics 20(5): 7862-7870 (2024) - [j9]Bo Chen
A Comprehensive Survey on Automated Machine Learning for Recommendations. Trans. Recomm. Syst. 2(2): 13:1-13:38 (2024) - [c59]Pengyue Jia
D3: A Methodological Exploration of Domain Division, Modeling, and Balance in Multi-Domain Recommendations. AAAI 2024: 8553-8561 - [c58]Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang:
HierRec: Scenario-Aware Hierarchical Modeling for Multi-scenario Recommendations. CIKM 2024: 653-662 - [c57]Yuening Wang, Man Chen, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates:
Enhancing Click-through Rate Prediction in Recommendation Domain with Search Query Representation. CIKM 2024: 2462-2471 - [c56]Yuhao Wang, Yichao Wang, Zichuan Fu, Xiangyang Li, Wanyu Wang, Yuyang Ye, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation. CIKM 2024: 2472-2481 - [c55]Pengyue Jia
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems. KDD 2024: 5194-5205 - [c54]Yang Yang
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising. RecSys 2024: 633-642 - [c53]Yuhao Wang, Ziru Liu, Yichao Wang, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang:
Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation. WSDM 2024: 779-787 - [c52]Zirui Zhu
Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization. WWW 2024: 3485-3496 - [i42]Zirui Zhu, Yong Liu, Zangwei Zheng, Huifeng Guo, Yang You:
Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization. CoRR abs/2403.00798 (2024) - [i41]Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems. CoRR abs/2403.12660 (2024) - [i40]Wenlin Zhang, Chuhan Wu
Tired of Plugins? Large Language Models Can Be End-To-End Recommenders. CoRR abs/2404.00702 (2024) - [i39]Jingtong Gao, Bo Chen, Xiangyu Zhao, Weiwen Liu, Xiangyang Li, Yichao Wang, Zijian Zhang, Wanyu Wang, Yuyang Ye, Shanru Lin, Huifeng Guo, Ruiming Tang
LLM-enhanced Reranking in Recommender Systems. CoRR abs/2406.12433 (2024) - [i38]Yuhao Wang, Yichao Wang, Zichuan Fu, Xiangyang Li, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation. CoRR abs/2406.12529 (2024) - [i37]Bo Chen, Xinyi Dai
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era. CoRR abs/2407.10081 (2024) - [i36]Shiwei Li, Huifeng Guo, Xing Tang, Ruiming Tang
Embedding Compression in Recommender Systems: A Survey. CoRR abs/2408.02304 (2024) - [i35]Yusheng Lu, Zhaocheng Du, Xiangyang Li, Xiangyu Zhao, Weiwen Liu, Yichao Wang, Huifeng Guo, Ruiming Tang
Prompt Tuning as User Inherent Profile Inference Machine. CoRR abs/2408.06577 (2024) - [i34]Yang Yang, Bo Chen, Chenxu Zhu, Menghui Zhu, Xinyi Dai, Huifeng Guo, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising. CoRR abs/2408.07907 (2024) - 2023
- [c51]Shiwei Li
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. AAAI 2023: 4435-4443 - [c50]Huan Wang, Huifeng Guo, Zehui Mao, Haibin Li, Qiang Qu, Yulei Yang:
Bidirectional Mapping RTE for Fault Knowledge Graph Construction. SAFEPROCESS 2023: 1-6 - [c49]Xiaopeng Li
HAMUR: Hyper Adapter for Multi-Domain Recommendation. CIKM 2023: 1268-1277 - [c48]Qidong Liu
Diffusion Augmentation for Sequential Recommendation. CIKM 2023: 1576-1586 - [c47]Wei Guo
DFFM: Domain Facilitated Feature Modeling for CTR Prediction. CIKM 2023: 4602-4608 - [c46]Chang Meng
Hierarchical Projection Enhanced Multi-behavior Recommendation. KDD 2023: 4649-4660 - [c45]Yejing Wang
Single-shot Feature Selection for Multi-task Recommendations. SIGIR 2023: 341-351 - [c44]Jingtong Gao
AutoTransfer: Instance Transfer for Cross-Domain Recommendations. SIGIR 2023: 1478-1487 - [c43]Yuhao Wang
PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations. SIGIR 2023: 1498-1507 - [c42]Chenxu Zhu
AutoGen: An Automated Dynamic Model Generation Framework for Recommender System. WSDM 2023: 598-606 - [c41]Ruiming Tang
AutoML for Deep Recommender Systems: Fundamentals and Advances. WSDM 2023: 1264-1267 - [c40]Wei Guo
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. WWW 2023: 960-970 - [i33]Yuhao Wang, Ha Tsz Lam, Yi Wong, Ziru Liu, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang
Multi-Task Deep Recommender Systems: A Survey. CoRR abs/2302.03525 (2023) - [i32]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. CoRR abs/2303.02418 (2023) - [i31]Jianghao Lin, Xinyi Dai
How Can Recommender Systems Benefit from Large Language Models: A Survey. CoRR abs/2306.05817 (2023) - [i30]Ziru Liu, Kecheng Chen, Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
AutoAssign+: Automatic Shared Embedding Assignment in Streaming Recommendation. CoRR abs/2308.06965 (2023) - [i29]Hengyu Zhang, Chang Meng, Wei Guo, Huifeng Guo, Jieming Zhu, Guangpeng Zhao, Ruiming Tang
Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction. CoRR abs/2308.09966 (2023) - [i28]Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang
Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation. CoRR abs/2309.02061 (2023) - [i27]Xiaopeng Li, Fan Yan, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang
HAMUR: Hyper Adapter for Multi-Domain Recommendation. CoRR abs/2309.06217 (2023) - [i26]Qidong Liu, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang
Diffusion Augmentation for Sequential Recommendation. CoRR abs/2309.12858 (2023) - [i25]Zichuan Fu, Xiangyang Li, Chuhan Wu
A Unified Framework for Multi-Domain CTR Prediction via Large Language Models. CoRR abs/2312.10743 (2023) - 2022
- [j8]Niannan Xue
AutoHash: Learning Higher-Order Feature Interactions for Deep CTR Prediction. IEEE Trans. Knowl. Data Eng. 34(6): 2653-2666 (2022) - [c39]Fuyuan Lyu
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CIKM 2022: 1399-1409 - [c38]Hengyu Zhang
Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks. CIKM 2022: 2549-2558 - [c37]Bo Chen
Numerical Feature Representation with Hybrid N-ary Encoding. CIKM 2022: 2984-2993 - [c36]Xiangyang Li, Bo Chen
IntTower: The Next Generation of Two-Tower Model for Pre-Ranking System. CIKM 2022: 3292-3301 - [c35]Wei Guo, Can Zhang
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. ICDE 2022: 727-740 - [c34]Fuyuan Lyu, Xing Tang
Memorize, Factorize, or be Naive: Learning Optimal Feature Interaction Methods for CTR Prediction. ICDE 2022: 1450-1462 - [c33]Fengyi Song, Bo Chen
AutoAssign: Automatic Shared Embedding Assignment in Streaming Recommendation. ICDM 2022: 458-467 - [c32]Yankai Chen, Yifei Zhang, Huifeng Guo, Ruiming Tang, Irwin King:
An Effective Post-training Embedding Binarization Approach for Fast Online Top-K Passage Matching. AACL/IJCNLP (2) 2022: 102-108 - [c31]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. KDD 2022: 168-178 - [c30]Zhicheng He, Wei Xia, Kai Dong, Huifeng Guo, Ruiming Tang
Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms. KDD 2022: 2997-3006 - [c29]Yichao Wang
CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation. KDD 2022: 4090-4099 - [c28]Enming Yuan, Wei Guo, Zhicheng He, Huifeng Guo, Chengkai Liu, Ruiming Tang
Multi-Behavior Sequential Transformer Recommender. SIGIR 2022: 1642-1652 - [c27]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [i24]Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang
Automated Machine Learning for Deep Recommender Systems: A Survey. CoRR abs/2204.01390 (2022) - [i23]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. CoRR abs/2206.02115 (2022) - [i22]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CoRR abs/2208.04482 (2022) - [i21]Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, Jinxing Liu, Zhenhua Dong, Ruiming Tang
IntTower: the Next Generation of Two-Tower Model for Pre-Ranking System. CoRR abs/2210.09890 (2022) - [i20]Hengyu Zhang
Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks. CoRR abs/2210.14577 (2022) - [i19]Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. CoRR abs/2212.05735 (2022) - 2021
- [c26]Qiming Zheng, Quan Chen, Kaihao Bai, Huifeng Guo, Yong Gao, Xiuqiang He, Minyi Guo:
BiPS: Hotness-aware Bi-tier Parameter Synchronization for Recommendation Models. IPDPS 2021: 609-618 - [c25]Wei Guo, Rong Su, Renhao Tan
Dual Graph enhanced Embedding Neural Network for CTR Prediction. KDD 2021: 496-504 - [c24]Huifeng Guo, Bo Chen
An Embedding Learning Framework for Numerical Features in CTR Prediction. KDD 2021: 2910-2918 - [c23]Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table. SIGIR 2021: 1269-1278 - [i18]Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang, Xiuqiang He, Wenzhi Liu:
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table. CoRR abs/2104.08542 (2021) - [i17]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. CoRR abs/2106.00314 (2021) - [i16]Fuyuan Lyu, Xing Tang, Huifeng Guo, Ruiming Tang, Xiuqiang He, Rui Zhang, Xue Liu:
Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction. CoRR abs/2108.01265 (2021) - [i15]Yong Gao, Huifeng Guo, Dandan Lin, Yingxue Zhang, Ruiming Tang, Xiuqiang He:
Content Filtering Enriched GNN Framework for News Recommendation. CoRR abs/2110.12681 (2021) - [i14]Wei Guo, Can Zhang, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang:
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. CoRR abs/2111.15068 (2021) - [i13]Yankai Chen, Yifei Zhang, Yingxue Zhang, Huifeng Guo, Jingjie Li, Ruiming Tang, Xiuqiang He, Irwin King:
Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation. CoRR abs/2112.01944 (2021) - 2020
- [j7]Feng Liu, Ruiming Tang
Top-aware reinforcement learning based recommendation. Neurocomputing 417: 255-269 (2020) - [j6]Feng Liu, Ruiming Tang
State representation modeling for deep reinforcement learning based recommendation. Knowl. Based Syst. 205: 106170 (2020) - [c22]Hui Yang, Jingwen Nan
Representation Learning-based Slice Resource Reconfiguring Scheme in Multimedia Networks. BMSB 2020: 1-3 - [c21]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CIKM 2020: 2861-2868 - [c20]Chao Li, Hui Yang, Bowen Bao, Huifeng Guo, Yong Jiang, Jie Zhang:
Spearman Correlation Coefficient Abnormal Behavior Monitoring Technology Based on RNN in 5G Network for Smart City. IWCMC 2020: 1440-1442 - [c19]Jianing Sun, Wei Guo
A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. KDD 2020: 2030-2039 - [c18]Bin Liu, Niannan Xue, Huifeng Guo, Ruiming Tang
AutoGroup: Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction. SIGIR 2020: 199-208 - [c17]Jianing Sun, Yingxue Zhang, Wei Guo
Neighbor Interaction Aware Graph Convolution Networks for Recommendation. SIGIR 2020: 1289-1298 - [c16]Wei Guo, Can Zhang
Multi-Branch Convolutional Network for Context-Aware Recommendation. SIGIR 2020: 1709-1712 - [c15]Feng Liu, Huifeng Guo, Xutao Li, Ruiming Tang
End-to-End Deep Reinforcement Learning based Recommendation with Supervised Embedding. WSDM 2020: 384-392 - [c14]Feng Liu, Wei Guo, Huifeng Guo, Ruiming Tang
Dual-attentional Factorization-Machines based Neural Network for User Response Prediction. WWW (Companion Volume) 2020: 26-27 - [i12]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Graph Convolution Collaborative Filtering. CoRR abs/2001.00267 (2020) - [i11]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CoRR abs/2008.13517 (2020) - [i10]Yichao Wang
A Practical Incremental Method to Train Deep CTR Models. CoRR abs/2009.02147 (2020) - [i9]Huifeng Guo, Bo Chen, Ruiming Tang, Zhenguo Li, Xiuqiang He:
AutoDis: Automatic Discretization for Embedding Numerical Features in CTR Prediction. CoRR abs/2012.08986 (2020)
2010 – 2019
- 2019
- [j5]Ao Yu
Accurate Fault Location Using Deep Belief Network for Optical Fronthaul Networks in 5G and Beyond. IEEE Access 7: 77932-77943 (2019) - [j4]Ao Yu, Jie Zhang, Hui Yang, Ting Xu, Baoguo Yu, Qiuyan Yao, Yajie Li, Tao Peng, Huifeng Guo, Jun Li:
Long-Term Traffic Scheduling Based on Stacked Bidirectional Recurrent Neural Networks in Inter-Datacenter Optical Networks. IEEE Access 7: 182296-182308 (2019) - [j3]Yanru Qu, Bohui Fang, Weinan Zhang, Ruiming Tang
Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data. ACM Trans. Inf. Syst. 37(1): 5:1-5:35 (2019) - [c13]Jianing Sun, Yingxue Zhang, Chen Ma
Multi-graph Convolution Collaborative Filtering. ICDM 2019: 1306-1311 - [c12]Jingwen Nan, Hui Yang, Ao Yu, Yajie Li, Huifeng Guo, Tao Peng, Jie Zhang:
Slice-Scaling Strategy Based on Representation Learning in Flex-Grid Optical Networks. OFC 2019: 1-3 - [c11]Ao Yu, Hui Yang, Qiuyan Yao, Yajie Li, Huifeng Guo, Tao Peng, Haibin Li, Jie Zhang:
Scheduling with Flow Prediction Based on Time and Frequency 2D Classification for Hybrid Electrical/Optical Intra-Datacenter Networks. OFC 2019: 1-3 - [c10]Xudong Zhao, Hui Yang, Huifeng Guo, Tao Peng, Jie Zhang:
Accurate Fault Location based on Deep Neural Evolution Network in Optical Networks for 5G and Beyond. OFC 2019: 1-3 - [c9]Huifeng Guo, Ruiming Tang
A Novel KNN Approach for Session-Based Recommendation. PAKDD (2) 2019: 381-393 - [c8]Huifeng Guo, Jinkai Yu, Qing Liu, Ruiming Tang
PAL: a position-bias aware learning framework for CTR prediction in live recommender systems. RecSys 2019: 452-456 - [c7]Wei Guo, Ruiming Tang
Order-aware Embedding Neural Network for CTR Prediction. SIGIR 2019: 1121-1124 - [c6]Bin Liu, Ruiming Tang
Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction. WWW 2019: 1119-1129 - [i8]Bin Liu, Ruiming Tang, Yingzhi Chen, Jinkai Yu, Huifeng Guo, Yuzhou Zhang:
Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction. CoRR abs/1904.04447 (2019) - 2018
- [c5]Feng Liu, Ruiming Tang
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification. DASFAA (2) 2018: 184-200 - [c4]Weiwen Liu
Field-aware probabilistic embedding neural network for CTR prediction. RecSys 2018: 412-416 - [i7]Feng Liu, Ruiming Tang, Xutao Li, Yunming Ye, Huifeng Guo, Xiuqiang He:
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification. CoRR abs/1802.08401 (2018) - [i6]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He, Zhenhua Dong:
DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction. CoRR abs/1804.04950 (2018) - [i5]Yanru Qu, Bohui Fang, Weinan Zhang, Ruiming Tang, Minzhe Niu, Huifeng Guo, Yong Yu, Xiuqiang He:
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data. CoRR abs/1807.00311 (2018) - [i4]Huifeng Guo, Ruiming Tang, Yunming Ye, Feng Liu, Yuzhou Zhang:
An Adjustable Heat Conduction based KNN Approach for Session-based Recommendation. CoRR abs/1807.05739 (2018) - [i3]Feng Liu, Ruiming Tang, Xutao Li, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang:
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling. CoRR abs/1810.12027 (2018) - 2017
- [c3]Huifeng Guo, Ruiming Tang
A Graph-Based Push Service Platform. DASFAA (2) 2017: 636-648 - [c2]Huifeng Guo, Ruiming Tang
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. IJCAI 2017: 1725-1731 - [c1]Huifeng Guo, Ruiming Tang
Holistic Neural Network for CTR Prediction. WWW (Companion Volume) 2017: 787-788 - [i2]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. CoRR abs/1703.04247 (2017) - 2016
- [j2]Huifeng Guo, Dian-Hui Chu, Yunming Ye, Xutao Li, Xixian Fan:
BLM-Rank: A Bayesian Linear Method for Learning to Rank and Its GPU Implementation. IEICE Trans. Inf. Syst. 99-D(4): 896-905 (2016) - [i1]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
A Graph-based Push Service Platform. CoRR abs/1611.09496 (2016) - 2014
- [j1]Xiaohui Huang, Yunming Ye, Huifeng Guo, Yi Cai, Haijun Zhang, Yan Li:
DSKmeans: A new kmeans-type approach to discriminative subspace clustering. Knowl. Based Syst. 70: 293-300 (2014)
Coauthor Index
[j12] [j11] [j9] [c59] [c58] [c56] [c55] [c54] [c53] [i41] [i40] [i39] [i38] [i37] [i36] [i35] [i34] [c51] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [i33] [i32] [i31] [i30] [i29] [i28] [i27] [i26] [i25] [j8] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [i24] [i23] [i22] [i21] [i20] [i19] [c25] [c24] [c23] [i18] [i17] [i16] [i15] [i14] [i13] [j7] [j6] [c21] [c19] [c18] [c17] [c16] [c15] [c14] [i12] [i11] [i10] [i9] [j3] [c13] [c9] [c8] [c7] [c6] [i8] [c5] [c4] [i7] [i6] [i5] [i4] [i3] [c3] [c2] [c1] [i2] [i1]
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