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ORCIDGeorge Forman
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2020 – today
- 2021
[c29]Karan Matnani, Valerie Liptak, George Forman:
What's Mine is Yours, What's Yours is Mine: Simplifying Significance Testing With Big Data. EDBT/ICDT Workshops 2021- [c28]George Forman
:
Getting Your Package to the Right Place: Supervised Machine Learning for Geolocation. ECML/PKDD (4) 2021: 403-419
2010 – 2019
- 2015
- [j9]Yanmin Zhu, Yin Wang, George Forman, Hong Wei:
Mining Large-Scale GPS Streams for Connectivity Refinement of Road Maps. Comput. J. 58(9): 2109-2119 (2015) - [c27]George Forman, Hila Nachlieli, Renato Keshet:
Clustering by Intent: A Semi-Supervised Method to Discover Relevant Clusters Incrementally. ECML/PKDD (3) 2015: 20-36 - 2013
- [c26]Hong Wei, Yin Wang, George Forman, Yanmin Zhu:
Map matching: comparison of approaches using sparse and noisy data. SIGSPATIAL/GIS 2013: 434-437 - [c25]Yin Wang, Hong Wei, George Forman:
Mining large-scale gps streams for connectivity refinement of road maps. SIGSPATIAL/GIS 2013: 438-441 - [c24]Yin Wang, Xuemei Liu, Hong Wei, George Forman, Chao Chen, Yanmin Zhu:
CrowdAtlas: self-updating maps for cloud and personal use. MobiSys 2013: 27-40 - [c23]Yin Wang, Xuemei Liu, Hong Wei, George Forman, Yanmin Zhu:
CrowdAtlas: self-updating maps for cloud and personal use. MobiSys 2013: 469-470 - 2012
- [c22]Hong Wei, Yin Wang, George Forman, Yanmin Zhu, Haibing Guan:
Fast Viterbi map matching with tunable weight functions. SIGSPATIAL/GIS 2012: 613-616 - [c21]Xuemei Liu, James Biagioni, Jakob Eriksson, Yin Wang, George Forman, Yanmin Zhu:
Mining large-scale, sparse GPS traces for map inference: comparison of approaches. KDD 2012: 669-677 - [c20]Evan Kirshenbaum, George Forman, Michael Dugan:
A Live Comparison of Methods for Personalized Article Recommendation at Forbes.com. ECML/PKDD (2) 2012: 51-66 - [c19]George Forman:
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable. SDM 2012: 485-493 - 2010
- [j8]George Forman, Martin Scholz:
Apples-to-apples in cross-validation studies: pitfalls in classifier performance measurement. SIGKDD Explor. 12(1): 49-57 (2010) - [c18]George Forman, Evan Kirshenbaum, Shyamsundar Rajaram:
A novel traffic analysis for identifying search fields in the long tail of web sites. WWW 2010: 361-370
2000 – 2009
- 2009
- [j7]George Forman, Kave Eshghi, Jaap Suermondt:
Efficient detection of large-scale redundancy in enterprise file systems. ACM SIGOPS Oper. Syst. Rev. 43(1): 84-91 (2009) - [c17]George Forman, Martin Scholz, Shyamsundar Rajaram:
Feature shaping for linear SVM classifiers. KDD 2009: 299-308 - 2008
- [j6]George Forman:
Quantifying counts and costs via classification. Data Min. Knowl. Discov. 17(2): 164-206 (2008) - [c16]George Forman:
BNS feature scaling: an improved representation over tf-idf for svm text classification. CIKM 2008: 263-270 - [c15]George Forman, Evan Kirshenbaum:
Extremely fast text feature extraction for classification and indexing. CIKM 2008: 1221-1230 - [c14]George Forman, Shyamsundar Rajaram:
Scaling up text classification for large file systems. KDD 2008: 239-246 - 2007
- [c13]Cullen E. Bash, George Forman:
Cool Job Allocation: Measuring the Power Savings of Placing Jobs at Cooling-Efficient Locations in the Data Center. USENIX ATC 2007: 363-368 - 2006
- [c12]George Forman:
Quantifying trends accurately despite classifier error and class imbalance. KDD 2006: 157-166 - [c11]George Forman, Evan Kirshenbaum, Jaap Suermondt:
Pragmatic text mining: minimizing human effort to quantify many issues in call logs. KDD 2006: 852-861 - [c10]George Forman:
Tackling concept drift by temporal inductive transfer. SIGIR 2006: 252-259 - 2005
- [j5]Huan Liu, Edward R. Dougherty, Jennifer G. Dy, Kari Torkkola, Eugene Tuv, Hanchuan Peng, Chris H. Q. Ding, Fuhui Long, Michael E. Berens, Lance Parsons, Zheng Zhao, Lei Yu, George Forman:
Evolving Feature Selection. IEEE Intell. Syst. 20(6): 64-76 (2005) - [c9]George Forman, Ira Cohen:
Beware the Null Hypothesis: Critical Value Tables for Evaluating Classifiers. ECML 2005: 133-145 - [c8]George Forman:
Counting Positives Accurately Despite Inaccurate Classification. ECML 2005: 564-575 - [c7]George Forman, Kave Eshghi, Stephane Chiocchetti:
Finding similar files in large document repositories. KDD 2005: 394-400 - 2004
- [c6]George Forman:
A pitfall and solution in multi-class feature selection for text classification. ICML 2004 - [c5]George Forman, Ira Cohen:
Learning from Little: Comparison of Classifiers Given Little Training. PKDD 2004: 161-172 - 2003
- [j4]George Forman:
An Extensive Empirical Study of Feature Selection Metrics for Text Classification. J. Mach. Learn. Res. 3: 1289-1305 (2003) - 2002
- [j3]George Forman:
Feature Engineering for a Gene Regulation Prediction Task. SIGKDD Explor. 4(2): 106-107 (2002) - [c4]George Forman:
Incremental Machine Learning to Reduce Biochemistry Lab Costs in the Search for Drug Discovery. BIOKDD 2002: 33-36 - [c3]George Forman:
Choose Your Words Carefully: An Empirical Study of Feature Selection Metrics for Text Classification. PKDD 2002: 150-162 - 2000
- [j2]George Forman, Bin Zhang:
Distributed Data Clustering Can Be Efficient and Exact. SIGKDD Explor. 2(2): 34-38 (2000) - [c2]Bin Zhang, Meichun Hsu, George Forman:
Accurate Recasting of Parameter Estimation Algorithms Using Sufficient Statistics for Efficient Parallel Speed-Up: Demonstrated for Center-Based Data Clustering Algorithms. PKDD 2000: 243-254
1990 – 1999
- 1999
- [d1]Mark Hopkins, Erik Reeber, George Forman, Jaap Suermondt:
Spambase. UCI Machine Learning Repository, 1999
- 1994
- [j1]George Forman, John Zahorjan:
The Challenges of Mobile Computing. Computer 27(4): 38-47 (1994) - 1993
- [c1]Janice E. Cuny, George Forman, Alfred Hough, Joydip Kundu, Calvin Lin, Lawrence Snyder, David W. Stemple:
The Ariadne Debugger: Scalable Application of Event-Based Abstraction. Workshop on Parallel and Distributed Debugging 1993: 85-95
Coauthor Index
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