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ORCIDClaudia Perlich
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- affiliation: Dstillery, USA
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2020 – today
- 2023
[e3]Gianmarco De Francisci Morales
, Claudia Perlich, Natali Ruchansky, Nicolas Kourtellis, Elena Baralis, Francesco Bonchi:
Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VI. Lecture Notes in Computer Science 14174, Springer 2023, ISBN 978-3-031-43426-6 [contents]- [e2]Gianmarco De Francisci Morales, Claudia Perlich, Natali Ruchansky, Nicolas Kourtellis, Elena Baralis, Francesco Bonchi:
Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VII. Lecture Notes in Computer Science 14175, Springer 2023, ISBN 978-3-031-43429-7 [contents]
2010 – 2019
- 2018
- [c22]Yeming Shi, Claudia Perlich, Rod Hook, Wickus Martin, Melinda Han Williams, Justin Moynihan, Patrick McCarthy, Peter Lenz, Reka Daniel-Weiner, Roger Cost:
Audience Size Forecasting: Fast and Smart Budget Planning for Media Buyers. KDD 2018: 744-753 - 2017
- [c21]Yeming Shi, Ori Stitelman, Claudia Perlich:
Blacklisting the Blacklist in Online Advertising: Improving Delivery by Bidding for What You Can Win. ADKDD@KDD 2017: 1:1-1:6 - [r3]Claudia Perlich:
Learning Curves in Machine Learning. Encyclopedia of Machine Learning and Data Mining 2017: 708-711 - 2016
- [c20]Claudia Perlich:
Automated Machine Learning in the Wild. RecSys 2016: 1 - 2015
- [j15]Brian Dalessandro, Rod Hook, Claudia Perlich, Foster J. Provost:
Evaluating and Optimizing Online Advertising: Forget the Click, but There Are Good Proxies. Big Data 3(2): 90-102 (2015) - 2014
- [j14]Brian Dalessandro, Claudia Perlich, Troy Raeder:
Bigger is Better, but at What Cost?Estimating the Economic Value of Incremental Data Assets. Big Data 2(2): 87-96 (2014) - [j13]Foster J. Provost, Geoffrey I. Webb, Ron Bekkerman, Oren Etzioni, Usama M. Fayyad, Claudia Perlich:
A Data Scientist's Guide to Start-Ups. Big Data 2(3): 117-128 (2014) - [j12]Claudia Perlich, Brian Dalessandro, Troy Raeder, Ori Stitelman, Foster J. Provost:
Machine learning for targeted display advertising: transfer learning in action. Mach. Learn. 95(1): 103-127 (2014) - [c19]Melinda Han Williams, Claudia Perlich, Brian Dalessandro, Foster J. Provost:
Pleasing the advertising oracle: Probabilistic prediction from sampled, aggregated ground truth. ADKDD@KDD 2014: 3:1-3:9 - [c18]Brian Dalessandro, Daizhuo Chen, Troy Raeder, Claudia Perlich, Melinda Han Williams, Foster J. Provost:
Scalable hands-free transfer learning for online advertising. KDD 2014: 1573-1582 - [e1]Sofus A. Macskassy, Claudia Perlich, Jure Leskovec, Wei Wang, Rayid Ghani:
The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '14, New York, NY, USA - August 24 - 27, 2014. ACM 2014, ISBN 978-1-4503-2956-9 [contents] - 2013
- [c17]Martine De Cock, Senjuti Basu Roy, Swapna Savvana, Vani Mandava, Brian Dalessandro, Claudia Perlich, William Cukierski, Benjamin Hamner:
The Microsoft Academic Search challenges at KDD Cup 2013. IEEE BigData 2013: 1-4 - [c16]Senjuti Basu Roy, Martine De Cock, Vani Mandava, Swapna Savanna, Brian Dalessandro, Claudia Perlich, William Cukierski, Ben Hamner:
The Microsoft academic search dataset and KDD Cup 2013. KDD Cup 2013: 1:1-1:6 - [c15]Troy Raeder, Claudia Perlich, Brian Dalessandro, Ori Stitelman, Foster J. Provost:
Scalable supervised dimensionality reduction using clustering. KDD 2013: 1213-1221 - [c14]Ori Stitelman, Claudia Perlich, Brian Dalessandro, Rod Hook, Troy Raeder, Foster J. Provost:
Using co-visitation networks for detecting large scale online display advertising exchange fraud. KDD 2013: 1240-1248 - 2012
- [j11]Shachar Kaufman, Saharon Rosset, Claudia Perlich, Ori Stitelman:
Leakage in data mining: Formulation, detection, and avoidance. ACM Trans. Knowl. Discov. Data 6(4): 15:1-15:21 (2012) - [c13]Brian Dalessandro, Claudia Perlich, Ori Stitelman, Foster J. Provost:
Causally motivated attribution for online advertising. AdKDD@KDD 2012: 7:1-7:9 - [c12]Claudia Perlich, Brian Dalessandro, Rod Hook, Ori Stitelman, Troy Raeder, Foster J. Provost:
Bid optimizing and inventory scoring in targeted online advertising. KDD 2012: 804-812 - [c11]Troy Raeder, Ori Stitelman, Brian Dalessandro, Claudia Perlich, Foster J. Provost:
Design principles of massive, robust prediction systems. KDD 2012: 1357-1365 - 2011
- [c10]Shachar Kaufman, Saharon Rosset, Claudia Perlich:
Leakage in data mining: formulation, detection, and avoidance. KDD 2011: 556-563 - [c9]Yan Liu, Pei-yun Hseuh, Rick Lawrence, Steve Meliksetian, Claudia Perlich, Alejandro Veen:
Latent graphical models for quantifying and predicting patent quality. KDD 2011: 1145-1153 - 2010
- [j10]Saharon Rosset, Claudia Perlich, Grzegorz Swirszcz, Prem Melville, Yan Liu:
Medical data mining: insights from winning two competitions. Data Min. Knowl. Discov. 20(3): 439-468 (2010) - [j9]Rick Lawrence, Claudia Perlich, Saharon Rosset, Ildar Khabibrakhmanov, Shilpa Mahatma, Sholom M. Weiss, Matthew Callahan, Matt Collins, Alexey Ershov, Shiva Kumar:
Operations Research Improves Sales Force Productivity at IBM. Interfaces 40(1): 33-46 (2010) - [j8]Claudia Perlich, Grzegorz Swirszcz:
On cross-validation and stacking: building seemingly predictive models on random data. SIGKDD Explor. 12(2): 11-15 (2010) - [r2]Claudia Perlich:
Learning Curves in Machine Learning. Encyclopedia of Machine Learning 2010: 577-580
2000 – 2009
- 2009
- [c8]Aurélie C. Lozano, Hongfei Li, Alexandru Niculescu-Mizil, Yan Liu, Claudia Perlich, Jonathan R. M. Hosking, Naoki Abe:
Spatial-temporal causal modeling for climate change attribution. KDD 2009: 587-596 - [c7]Alexandru Niculescu-Mizil, Claudia Perlich, Grzegorz Swirszcz, Vikas Sindhwani, Yan Liu, Prem Melville, Dong Wang, Jing Xiao, Jianying Hu, Moninder Singh, Wei Xiong Shang, Yanfeng Zhu:
Winning the KDD Cup Orange Challenge with Ensemble Selection. KDD Cup 2009: 23-34 - [r1]Claudia Perlich, Saharon Rosset, Bianca Zadrozny:
Modeling Quantiles. Encyclopedia of Data Warehousing and Mining 2009: 1324-1329 - 2008
- [j7]Claudia Perlich, Prem Melville, Yan Liu, Grzegorz Swirszcz, Richard D. Lawrence, Saharon Rosset:
Breast cancer identification: KDD CUP winner's report. SIGKDD Explor. 10(2): 39-42 (2008) - 2007
- [j6]Richard D. Lawrence, Claudia Perlich, Saharon Rosset, Jorge Arroyo, Matthew Callahan, J. Matthew Collins, Alexey Ershov, Sheri Feinzig, Ildar Khabibrakhmanov, Shilpa Mahatma, Mark Niemaszyk, Sholom M. Weiss:
Analytics-driven solutions for customer targeting and sales-force allocation. IBM Syst. J. 46(4): 797-816 (2007) - [j5]Saharon Rosset, Claudia Perlich, Bianca Zadrozny:
Ranking-based evaluation of regression models. Knowl. Inf. Syst. 12(3): 331-353 (2007) - [j4]Saharon Rosset, Claudia Perlich, Yan Liu:
Making the most of your data: KDD Cup 2007 "How Many Ratings" winner's report. SIGKDD Explor. 9(2): 66-69 (2007) - [c6]Wojciech Gryc, Mary E. Helander, Richard D. Lawrence, Yan Liu, Claudia Perlich, Chandan K. Reddy, Saharon Rosset:
Looking for Great Ideas: Analyzing the Innovation Jam. WebKDD/SNA-KDD 2007: 21-39 - [c5]Claudia Perlich, Saharon Rosset, Richard D. Lawrence, Bianca Zadrozny:
High-quantile modeling for customer wallet estimation and other applications. KDD 2007: 977-985 - [c4]Claudia Perlich, Saharon Rosset:
Identifying Bundles of Product Options using Mutual Information Clustering. SDM 2007: 390-397 - 2006
- [j3]Claudia Perlich, Foster J. Provost:
Distribution-based aggregation for relational learning with identifier attributes. Mach. Learn. 62(1-2): 65-105 (2006) - [c3]Srujana Merugu, Saharon Rosset, Claudia Perlich:
A new multi-view regression approach with an application to customer wallet estimation. KDD 2006: 656-661 - 2005
- [c2]Saharon Rosset, Claudia Perlich, Bianca Zadrozny:
Ranking-Based Evaluation of Regression Models. ICDM 2005: 370-377 - 2003
- [j2]Claudia Perlich, Foster J. Provost, Jeffrey S. Simonoff:
Tree Induction vs. Logistic Regression: A Learning-Curve Analysis. J. Mach. Learn. Res. 4: 211-255 (2003) - [j1]Claudia Perlich, Foster J. Provost, Sofus A. Macskassy:
Predicting citation rates for physics papers: constructing features for an ordered probit model. SIGKDD Explor. 5(2): 154-155 (2003) - [c1]Claudia Perlich, Foster J. Provost:
Aggregation-based feature invention and relational concept classes. KDD 2003: 167-176
Coauthor Index
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