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ORCIDGeorge Karypis
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- affiliation: University of Minnesota, USA
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2020 – today
- 2021
[i31]Shalini Pandey, Andrew Lan, George Karypis, Jaideep Srivastava:
Learning Student Interest Trajectory for MOOCThread Recommendation. CoRR abs/2101.05625 (2021)- [i30]Shalini Pandey, George Karypis, Jaideep Srivastava:
An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset. CoRR abs/2101.06373 (2021) - [i29]Balasubramaniam Srinivasan, Da Zheng, George Karypis:
Learning over Families of Sets - Hypergraph Representation Learning for Higher Order Tasks. CoRR abs/2101.07773 (2021) - 2020
- [j79]Athanasios N. Nikolakopoulos, George Karypis:
Boosting Item-based Collaborative Filtering via Nearly Uncoupled Random Walks. ACM Trans. Knowl. Discov. Data 14(6): 64:1-64:26 (2020) - [c172]Saurav Manchanda, George Karypis:
CAWA: An Attention-Network for Credit Attribution. AAAI 2020: 8472-8479 - [c171]George Karypis:
GrAPL 2020 Keynote Speaker Deep Graph Library: Overview, Updates, and Future Developments. IPDPS Workshops 2020: 201 - [c170]Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis:
Scalable Graph Neural Networks with Deep Graph Library. KDD 2020: 3521-3522 - [c169]Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis:
DGL-KE: Training Knowledge Graph Embeddings at Scale. SIGIR 2020: 739-748 - [c168]Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis:
Learning Graph Neural Networks with Deep Graph Library. WWW (Companion Volume) 2020: 305-306 - [i28]Sara Morsy, George Karypis:
Context-aware Non-linear and Neural Attentive Knowledge-based Models for Grade Prediction. CoRR abs/2003.05063 (2020) - [i27]Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis:
DGL-KE: Training Knowledge Graph Embeddings at Scale. CoRR abs/2004.08532 (2020) - [i26]Xiangxiang Zeng, Xiang Song, Tengfei Ma, Xiaoqin Pan, Yadi Zhou, Yuan Hou, Zheng Zhang, George Karypis, Feixiong Cheng:
Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning. CoRR abs/2005.10831 (2020) - [i25]Vassilis N. Ioannidis, Da Zheng, George Karypis:
Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing. CoRR abs/2007.10261 (2020) - [i24]Vassilis N. Ioannidis, Da Zheng, George Karypis:
PanRep: Universal node embeddings for heterogeneous graphs. CoRR abs/2007.10445 (2020) - [i23]Colby Wise, Vassilis N. Ioannidis, Miguel Romero Calvo, Xiang Song, George Price, Ninad Kulkarni, Ryan Brand, Parminder Bhatia, George Karypis:
COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature. CoRR abs/2007.12731 (2020) - [i22]Costas Mavromatis, George Karypis:
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning. CoRR abs/2009.06946 (2020) - [i21]Zeren Shui, George Karypis:
Heterogeneous Molecular Graph Neural Networks for Predicting Molecule Properties. CoRR abs/2009.12710 (2020) - [i20]Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis:
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR abs/2010.05337 (2020) - [i19]Maria Kalantzi, Agoritsa Polyzou, George Karypis:
FERN: Fair Team Formation for Mutually Beneficial Collaborative Learning. CoRR abs/2011.11611 (2020) - [i18]Saurav Manchanda, Mohit Sharma, George Karypis:
Distant-Supervised Slot-Filling for E-Commerce Queries. CoRR abs/2012.08134 (2020)
2010 – 2019
- 2019
- [j78]David C. Anastasiu
, George Karypis:
Parallel cosine nearest neighbor graph construction. J. Parallel Distributed Comput. 129: 61-82 (2019) - [j77]Mohit Sharma, F. Maxwell Harper, George Karypis:
Learning from Sets of Items in Recommender Systems. ACM Trans. Interact. Intell. Syst. 9(4): 19:1-19:26 (2019) - [j76]Agoritsa Polyzou, George Karypis:
Feature Extraction for Next-Term Prediction of Poor Student Performance. IEEE Trans. Learn. Technol. 12(2): 237-248 (2019) - [c167]Saurav Manchanda, Mohit Sharma, George Karypis:
Intent Term Weighting in E-commerce Queries. CIKM 2019: 2345-2348 - [c166]Sara Morsy, George Karypis:
Neural Attentive Knowledge-based Model for Grade Prediction. EDM 2019 - [c165]Shalini Pandey, George Karypis:
A Self Attentive model for Knowledge Tracing. EDM 2019 - [c164]Agoritsa Polyzou, Athanasios N. Nikolakopoulos, George Karypis:
Scholars Walk: A Markov Chain Framework for Course Recommendation. EDM 2019 - [c163]Shalini Pandey, George Karypis:
Structured Dictionary Learning for Energy Disaggregation. e-Energy 2019: 24-34 - [c162]Venkata Rohit Jakkula, George Karypis:
Streaming and Batch Algorithms for Truss Decomposition. GC 2019: 51-59 - [c161]Ancy Sarah Tom, George Karypis:
A 2D Parallel Triangle Counting Algorithm for Distributed-Memory Architectures. ICPP 2019: 45:1-45:10 - [c160]Sara Morsy, George Karypis:
A Study on Curriculum Planning and Its Relationship with Graduation GPA and Time To Degree. LAK 2019: 26-35 - [c159]Asmaa Elbadrawy, George Karypis:
UPM: Discovering Course Enrollment Sequences Associated with Success. LAK 2019: 373-382 - [c158]Prableen Kaur, Agoritsa Polyzou, George Karypis:
Causal Inference in Higher Education: Building Better Curriculums. L@S 2019: 49:1-49:4 - [c157]Athanasios N. Nikolakopoulos, Dimitris Berberidis, George Karypis, Georgios B. Giannakis:
Personalized diffusions for top-n recommendation. RecSys 2019: 260-268 - [c156]Athanasios N. Nikolakopoulos, George Karypis:
RecWalk: Nearly Uncoupled Random Walks for Top-N Recommendation. WSDM 2019: 150-158 - [c155]Mohit Sharma, George Karypis:
Adaptive matrix completion for the users and the items in tail. WWW 2019: 3223-3229 - [e11]Lisa Singh, Richard D. De Veaux, George Karypis, Francesco Bonchi, Jennifer Hill:
2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019, Washington, DC, USA, October 5-8, 2019. IEEE 2019, ISBN 978-1-7281-4493-1 [contents] - [e10]Ankur Teredesai, Vipin Kumar, Ying Li, Rómer Rosales, Evimaria Terzi, George Karypis:
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019. ACM 2019, ISBN 978-1-4503-6201-6 [contents] - [i17]Saurav Manchanda, George Karypis:
Distributed representation of multi-sense words: A loss-driven approach. CoRR abs/1904.06725 (2019) - [i16]Saurav Manchanda, George Karypis:
Text segmentation on multilabel documents: A distant-supervised approach. CoRR abs/1904.06730 (2019) - [i15]Sara Morsy, George Karypis:
Will this Course Increase or Decrease Your GPA? Towards Grade-aware Course Recommendation. CoRR abs/1904.11798 (2019) - [i14]Mohit Sharma, Jiayu Zhou, Junling Hu, George Karypis:
Feature-based factorized Bilinear Similarity Model for Cold-Start Top-n Item Recommendation. CoRR abs/1904.11799 (2019) - [i13]Mohit Sharma, George Karypis:
Adaptive Matrix Completion for the Users and the Items in Tail. CoRR abs/1904.11800 (2019) - [i12]Sara Morsy, George Karypis:
Sparse Neural Attentive Knowledge-based Models for Grade Prediction. CoRR abs/1904.11858 (2019) - [i11]Mohit Sharma, F. Maxwell Harper, George Karypis:
Learning from Sets of Items in Recommender Systems. CoRR abs/1904.12643 (2019) - [i10]Agoritsa Polyzou, George Karypis:
Grade prediction with course and student specific models. CoRR abs/1906.00792 (2019) - [i9]Shalini Pandey, George Karypis:
Structured Dictionary Learning for Energy Disaggregation. CoRR abs/1907.06581 (2019) - [i8]Shalini Pandey, George Karypis:
A Self-Attentive model for Knowledge Tracing. CoRR abs/1907.06837 (2019) - [i7]Ancy Sarah Tom, George Karypis:
A 2D Parallel Triangle Counting Algorithm for Distributed-Memory Architectures. CoRR abs/1907.09575 (2019) - [i6]Saurav Manchanda, Mohit Sharma, George Karypis:
Intent term selection and refinement in e-commerce queries. CoRR abs/1908.08564 (2019) - [i5]Venkata Rohit Jakkula, George Karypis:
Streaming and Batch Algorithms for Truss Decomposition. CoRR abs/1908.10550 (2019) - [i4]Athanasios N. Nikolakopoulos, George Karypis:
Boosting Item-based Collaborative Filtering via Nearly Uncoupled Random Walks. CoRR abs/1909.03579 (2019) - [i3]Saurav Manchanda, George Karypis:
CAWA: An Attention-Network for Credit Attribution. CoRR abs/1911.11358 (2019) - 2018
- [j75]Jeremy Iverson, George Karypis:
A virtual memory manager optimized for node-level cooperative multi-tasking in memory constrained systems. Int. J. High Perform. Comput. Appl. 32(5): 744-759 (2018) - [j74]Shaden Smith, Jongsoo Park, George Karypis:
HPC formulations of optimization algorithms for tensor completion. Parallel Comput. 74: 99-117 (2018) - [j73]Lisa Singh, Amol Deshpande, Wenchao Zhou, Arindam Banerjee, Alex J. Bowers, Sorelle A. Friedler, H. V. Jagadish, George Karypis, Zoran Obradovic, Anil Vullikanti, Wangda Zuo:
NSF BIGDATA PI Meeting - Domain-Specific Research Directions and Data Sets. SIGMOD Rec. 47(3): 32-35 (2018) - [c154]Agoritsa Polyzou, George Karypis:
Feature extraction for classifying students based on their academic performance. EDM 2018 - [c153]Saurav Manchanda, George Karypis:
Text Segmentation on Multilabel Documents: A Distant-Supervised Approach. ICDM 2018: 1170-1175 - [c152]Evangelia Christakopoulou, George Karypis:
Local Latent Space Models for Top-N Recommendation. KDD 2018: 1235-1243 - [c151]Saurav Manchanda, George Karypis:
Distributed Representation of Multi-sense Words: A Loss Driven Approach. PAKDD (2) 2018: 337-349 - [c150]Shaden Smith, Kejun Huang, Nicholas D. Sidiropoulos, George Karypis:
Streaming Tensor Factorization for Infinite Data Sources. SDM 2018: 81-89 - [c149]George Karypis:
Recent Advances in Recommender Systems: Sets, Local Models, Coverage, and Errors. WWW (Companion Volume) 2018: 1369 - [p9]Evangelia Christakopoulou, Shaden Smith, Mohit Sharma, Alex Richards, David C. Anastasiu, George Karypis:
Scalability and Distribution of Collaborative Recommenders. Collaborative Recommendations 2018: 369-404 - [r5]Ying Zhao, George Karypis:
Document Clustering. Encyclopedia of Database Systems (2nd ed.) 2018 - [i2]Zhuliu Li, Raphael Petegrosso, Shaden Smith, David Sterling, George Karypis, Rui Kuang:
Scalable Label Propagation for Multi-relational Learning on Tensor Product Graph. CoRR abs/1802.07379 (2018) - 2017
- [j72]David C. Anastasiu, George Karypis:
Efficient identification of Tanimoto nearest neighbors. Int. J. Data Sci. Anal. 4(3): 153-172 (2017) - [j71]Faisal M. Almutairi, Nicholas D. Sidiropoulos, George Karypis:
Context-Aware Recommendation-Based Learning Analytics Using Tensor and Coupled Matrix Factorization. IEEE J. Sel. Top. Signal Process. 11(5): 729-741 (2017) - [c148]Qian Hu, Agoritsa Polyzou, George Karypis, Huzefa Rangwala:
Enriching Course-Specific Regression Models with Content Features for Grade Prediction. DSAA 2017: 504-513 - [c147]Shaden Smith, George Karypis:
Accelerating the Tucker Decomposition with Compressed Sparse Tensors. Euro-Par 2017: 653-668 - [c146]Shaden Smith, Xing Liu, Nesreen K. Ahmed, Ancy Sarah Tom, Fabrizio Petrini, George Karypis:
Truss decomposition on shared-memory parallel systems. HPEC 2017: 1-6 - [c145]Ancy Sarah Tom, Narayanan Sundaram, Nesreen K. Ahmed, Shaden Smith, Stijn Eyerman, Midhunchandra Kodiyath, Ibrahim Hur, Fabrizio Petrini, George Karypis:
Exploring optimizations on shared-memory platforms for parallel triangle counting algorithms. HPEC 2017: 1-7 - [c144]Shaden Smith, Alec Beri, George Karypis:
Constrained Tensor Factorization with Accelerated AO-ADMM. ICPP 2017: 111-120 - [c143]Shaden Smith, Jongsoo Park, George Karypis:
Sparse Tensor Factorization on Many-Core Processors with High-Bandwidth Memory. IPDPS 2017: 1058-1067 - [c142]George Karypis:
Improving Higher Education: Learning Analytics & Recommender Systems Research. RecSys 2017: 2 - [c141]Sara Morsy, George Karypis:
Cumulative Knowledge-based Regression Models for Next-term Grade Prediction. SDM 2017: 552-560 - [e9]George Karypis, Jia Zhang:
2017 IEEE International Congress on Big Data, BigData Congress 2017, Honolulu, HI, USA, June 25-30, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-1996-4 [contents] - [e8]Vijay Raghavan, Srinivas Aluru, George Karypis, Lucio Miele, Xindong Wu:
2017 IEEE International Conference on Data Mining, ICDM 2017, New Orleans, LA, USA, November 18-21, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-3835-4 [contents] - [e7]Raju Gottumukkala, Xia Ning, Guozhu Dong, Vijay Raghavan, Srinivas Aluru, George Karypis, Lucio Miele, Xindong Wu:
2017 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2017, New Orleans, LA, USA, November 18-21, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-3800-2 [contents] - 2016
- [j70]Asmaa Elbadrawy, Agoritsa Polyzou, Zhiyun Ren, Mackenzie Sweeney, George Karypis, Huzefa Rangwala:
Predicting Student Performance Using Personalized Analytics. Computer 49(4): 61-69 (2016) - [j69]Agoritsa Polyzou, George Karypis:
Grade prediction with models specific to students and courses. Int. J. Data Sci. Anal. 2(3-4): 159-171 (2016) - [j68]Sara Morsy, George Karypis:
Accounting for Language Changes Over Time in Document Similarity Search. ACM Trans. Inf. Syst. 35(1): 1:1-1:26 (2016) - [c140]David C. Anastasiu, George Karypis:
Efficient Identification of Tanimoto Nearest Neighbors. DSAA 2016: 156-165 - [c139]Dominique LaSalle, George Karypis:
A Parallel Hill-Climbing Refinement Algorithm for Graph Partitioning. ICPP 2016: 236-241 - [c138]Shaden Smith, George Karypis:
A Medium-Grained Algorithm for Sparse Tensor Factorization. IPDPS 2016: 902-911 - [c137]Agoritsa Polyzou, George Karypis:
Grade Prediction with Course and Student Specific Models. PAKDD (1) 2016: 89-101 - [c136]Evangelia Christakopoulou, George Karypis:
Local Item-Item Models For Top-N Recommendation. RecSys 2016: 67-74 - [c135]Asmaa Elbadrawy, George Karypis:
Domain-Aware Grade Prediction and Top-n Course Recommendation. RecSys 2016: 183-190 - [c134]David C. Anastasiu, George Karypis:
Fast Parallel Cosine K-Nearest Neighbor Graph Construction. IA3@SC 2016: 50-53 - [c133]Shaden Smith, Jongsoo Park, George Karypis:
An exploration of optimization algorithms for high performance tensor completion. SC 2016: 359-371 - [e6]James Joshi, George Karypis, Ling Liu, Xiaohua Hu, Ronay Ak, Yinglong Xia, Weijia Xu, Aki-Hiro Sato, Sudarsan Rachuri, Lyle H. Ungar, Philip S. Yu, Rama Govindaraju, Toyotaro Suzumura:
2016 IEEE International Conference on Big Data, BigData 2016, Washington DC, USA, December 5-8, 2016. IEEE Computer Society 2016, ISBN 978-1-4673-9005-7 [contents] - 2015
- [j67]Dominique LaSalle, George Karypis:
Multi-threaded modularity based graph clustering using the multilevel paradigm. J. Parallel Distributed Comput. 76: 66-80 (2015) - [j66]Jeremy Iverson, Chandrika Kamath, George Karypis:
Evaluation of connected-component labeling algorithms for distributed-memory systems. Parallel Comput. 44: 53-68 (2015) - [j65]Asmaa Elbadrawy, George Karypis:
User-Specific Feature-Based Similarity Models for Top-n Recommendation of New Items. ACM Trans. Intell. Syst. Technol. 6(3): 33:1-33:20 (2015) - [j64]Rezwan Ahmed, George Karypis:
Algorithms for Mining the Coevolving Relational Motifs in Dynamic Networks. ACM Trans. Knowl. Discov. Data 10(1): 4:1-4:31 (2015) - [c132]David C. Anastasiu, George Karypis:
L2Knng: Fast Exact K-Nearest Neighbor Graph Construction with L2-Norm Pruning. CIKM 2015: 791-800 - [c131]Dominique LaSalle, George Karypis:
Efficient Nested Dissection for Multicore Architectures. Euro-Par 2015: 467-478 - [c130]David C. Anastasiu, Al Mamunur Rashid, Andrea Tagarelli, George Karypis:
Understanding computer usage evolution. ICDE 2015: 1549-1560 - [c129]Shaden Smith, Niranjay Ravindran, Nicholas D. Sidiropoulos, George Karypis:
SPLATT: Efficient and Parallel Sparse Tensor-Matrix Multiplication. IPDPS 2015: 61-70 - [c128]Asmaa Elbadrawy, R. Scott Studham, George Karypis:
Collaborative multi-regression models for predicting students' performance in course activities. LAK 2015: 103-107 - [c127]Xia Ning, George Karypis:
Recent Advances in Recommender Systems and Future Directions. PReMI 2015: 3-9 - [c126]Jeremy Iverson, George Karypis:
A Memory Management System Optimized for BDMPI's Memory and Execution Model. EuroMPI 2015: 2:1-2:10 - [c125]Shaden Smith, George Karypis:
Tensor-matrix products with a compressed sparse tensor. IA3@SC 2015: 5:1-5:7 - [c124]David C. Anastasiu, George Karypis:
PL2AP: fast parallel cosine similarity search. IA3@SC 2015: 8:1-8:8 - [c123]Dominique LaSalle, Md. Mostofa Ali Patwary, Nadathur Satish, Narayanan Sundaram, Pradeep Dubey, George Karypis:
Improving graph partitioning for modern graphs and architectures. IA3@SC 2015: 14:1-14:4 - [c122]Mohit Sharma, Jiayu Zhou, Junling Hu, George Karypis:
Feature-based factorized Bilinear Similarity Model for Cold-Start Top-n Item Recommendation. SDM 2015: 190-198 - [r4]Xia Ning, Christian Desrosiers, George Karypis:
A Comprehensive Survey of Neighborhood-Based Recommendation Methods. Recommender Systems Handbook 2015: 37-76 - 2014
- [j63]Dominique LaSalle, George Karypis:
MPI for Big Data: New tricks for an old dog. Parallel Comput. 40(10): 754-767 (2014) - [c121]Niranjay Ravindran, Nicholas D. Sidiropoulos, Shaden Smith, George Karypis:
Memory-efficient parallel computation of tensor and matrix products for big tensor decomposition. ACSSC 2014: 581-585 - [c120]Fan Yang, Xiaohui Yu, George Karypis:
Signaling adverse drug reactions with novel feature-based similarity model. BIBM 2014: 593-596 - [c119]William Myott, Thao Nguyen, Abhishek Chandra, George Karypis, Jon B. Weissman:
Opportunities for data-driven cloud-based mobile optimization. CTS 2014: 483-487 - [c118]Philip S. Yu, Masaru Kitsuregawa, Hiroshi Motoda, Bart Goethals, Minyi Guo, Longbing Cao, George Karypis, Irwin King, Wei Wang:
Welcome from DSAA 2014 chairs. DSAA 2014: 9-10 - [c117]David C. Anastasiu, George Karypis:
L2AP: Fast cosine similarity search with prefix L-2 norm bounds. ICDE 2014: 784-795 - [c116]Santosh Kabbur, George Karypis:
NLMF: NonLinear Matrix Factorization Methods for Top-N Recommender Systems. ICDM Workshops 2014: 167-174 - [c115]Evangelia Christakopoulou, George Karypis:
HOSLIM: Higher-Order Sparse LInear Method for Top-N Recommender Systems. PAKDD (2) 2014: 38-49 - [p8]David C. Anastasiu, Jeremy Iverson, Shaden Smith, George Karypis:
Big Data Frequent Pattern Mining. Frequent Pattern Mining 2014: 225-259 - 2013
- [j62]Andrea Tagarelli, George Karypis:
A segment-based approach to clustering multi-topic documents. Knowl. Inf. Syst. 34(3): 563-595 (2013) - [j61]Kevin W. DeRonne, George Karypis:
Pareto Optimal Pairwise Sequence Alignment. IEEE ACM Trans. Comput. Biol. Bioinform. 10(2): 481-493 (2013) - [j60]David C. Anastasiu, Byron J. Gao, Xing Jiang, George Karypis:
A novel two-box search paradigm for query disambiguation. World Wide Web 16(1): 1-29 (2013) - [c114]Roberto Interdonato, Salvatore Romeo, Andrea Tagarelli, George Karypis:
A Versatile Graph-Based Approach to Package Recommendation. ICTAI 2013: 857-864 - [c113]Dominique Lasalle, George Karypis:
Multi-threaded Graph Partitioning. IPDPS 2013: 225-236 - [c112]Santosh Kabbur, Xia Ning, George Karypis:
FISM: factored item similarity models for top-N recommender systems. KDD 2013: 659-667 - [c111]Zhonghua Jiang, George Karypis:
AREM: A Novel Associative Regression Model Based on EM Algorithm. PAKDD (1) 2013: 459-470 - [c110]Dominique LaSalle, George Karypis:
BDMPI: conquering BigData with small clusters using MPI. DISCS@SC 2013: 19-24 - [p7]David C. Anastasiu, Andrea Tagarelli, George Karypis:
Document Clustering: The Next Frontier. Data Clustering: Algorithms and Applications 2013: 305-338 - [e5]Hui Xiong, George Karypis, Bhavani M. Thuraisingham, Diane J. Cook, Xindong Wu:
2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013. IEEE Computer Society 2013, ISBN 978-0-7695-5108-1 [contents] - [e4]Wei Ding, Takashi Washio, Hui Xiong, George Karypis, Bhavani M. Thuraisingham, Diane J. Cook, Xindong Wu:
13th IEEE International Conference on Data Mining Workshops, ICDM Workshops, TX, USA, December 7-10, 2013. IEEE Computer Society 2013, ISBN 978-0-7695-5109-8 [contents] - [e3]Gaurav Pandey, Huzefa Rangwala, George Karypis, Jake Yue Chen, Mohammed Javeed Zaki:
Proceedings of the 12th International Workshop on Data Mining in Bioinformatics, BioKDD 2013, Chicago, IL, USA, August 11, 2013. ACM 2013, ISBN 978-1-4503-2327-7 [contents] - [e2]