Aggregation-based feature invention and relational concept classes. - Claudia Perlich; Foster J. Provost (KDD, 2003)

Tree Induction vs. Logistic Regression: A Learning-Curve Analysis. - Claudia Perlich; Foster J. Provost; Jeffrey S. Simonoff (J. Mach. Learn. Res., 2003)

Predicting citation rates for physics papers: constructing features for an ordered probit model. - Claudia Perlich; Foster J. Provost; Sofus A. Macskassy (SIGKDD Explor., 2003)

A new multi-view regression approach with an application to customer wallet estimation. - Srujana Merugu; Saharon Rosset; Claudia Perlich (KDD, 2006)

Distribution-based aggregation for relational learning with identifier attributes. - Claudia Perlich; Foster J. Provost (Mach. Learn., 2006)

Looking for Great Ideas: Analyzing the Innovation Jam. - Wojciech Gryc; Mary E. Helander; Richard D. Lawrence; Yan Liu 002; Claudia Perlich; Chandan K. Reddy; Saharon Rosset (WebKDD/SNA-KDD, 2007)

High-quantile modeling for customer wallet estimation and other applications. - Claudia Perlich; Saharon Rosset; Richard D. Lawrence; Bianca Zadrozny (KDD, 2007)

Identifying Bundles of Product Options using Mutual Information Clustering. - Claudia Perlich; Saharon Rosset (SDM, 2007)

Analytics-driven solutions for customer targeting and sales-force allocation. - 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 (IBM Syst. J., 2007)

Ranking-based evaluation of regression models. - Saharon Rosset; Claudia Perlich; Bianca Zadrozny (Knowl. Inf. Syst., 2007)

Making the most of your data: KDD Cup 2007 "How Many Ratings" winner's report. - Saharon Rosset; Claudia Perlich; Yan Liu 002 (SIGKDD Explor., 2007)

Breast cancer identification: KDD CUP winner's report. - Claudia Perlich; Prem Melville; Yan Liu 002; Grzegorz Swirszcz; Richard D. Lawrence; Saharon Rosset (SIGKDD Explor., 2008)

Spatial-temporal causal modeling for climate change attribution. - Aurélie C. Lozano; Hongfei Li; Alexandru Niculescu-Mizil; Yan Liu 002; Claudia Perlich; Jonathan R. M. Hosking; Naoki Abe (KDD, 2009)

Winning the KDD Cup Orange Challenge with Ensemble Selection. - Alexandru Niculescu-Mizil; Claudia Perlich; Grzegorz Swirszcz; Vikas Sindhwani; Yan Liu 002; Prem Melville; Dong Wang; Jing Xiao; Jianying Hu; Moninder Singh; Wei Xiong Shang; Yanfeng Zhu 001 (KDD Cup, 2009)

Modeling Quantiles. - Claudia Perlich; Saharon Rosset; Bianca Zadrozny (Encyclopedia of Data Warehousing and Mining, 2009)

Medical data mining: insights from winning two competitions. - Saharon Rosset; Claudia Perlich; Grzegorz Swirszcz; Prem Melville; Yan Liu 002 (Data Min. Knowl. Discov., 2010)

Operations Research Improves Sales Force Productivity at IBM. - Rick Lawrence; Claudia Perlich; Saharon Rosset; Ildar Khabibrakhmanov; Shilpa Mahatma; Sholom M. Weiss; Matthew Callahan; Matt Collins; Alexey Ershov; Shiva Kumar (Interfaces, 2010)

On cross-validation and stacking: building seemingly predictive models on random data. - Claudia Perlich; Grzegorz Swirszcz (SIGKDD Explor., 2010)

Learning Curves in Machine Learning. - Claudia Perlich (Encyclopedia of Machine Learning, 2010)

Leakage in data mining: formulation, detection, and avoidance. - Shachar Kaufman; Saharon Rosset; Claudia Perlich (KDD, 2011)

Latent graphical models for quantifying and predicting patent quality. - Yan Liu 002; Pei-yun Hseuh; Rick Lawrence; Steve Meliksetian; Claudia Perlich; Alejandro Veen (KDD, 2011)

Causally motivated attribution for online advertising. - Brian Dalessandro; Claudia Perlich; Ori Stitelman; Foster J. Provost (AdKDD@KDD, 2012)

Bid optimizing and inventory scoring in targeted online advertising. - Claudia Perlich; Brian Dalessandro; Rod Hook; Ori Stitelman; Troy Raeder; Foster J. Provost (KDD, 2012)

Design principles of massive, robust prediction systems. - Troy Raeder; Ori Stitelman; Brian Dalessandro; Claudia Perlich; Foster J. Provost (KDD, 2012)

Leakage in data mining: Formulation, detection, and avoidance. - Shachar Kaufman; Saharon Rosset; Claudia Perlich; Ori Stitelman (ACM Trans. Knowl. Discov. Data, 2012)

The Microsoft Academic Search challenges at KDD Cup 2013. - Martine De Cock; Senjuti Basu Roy; Swapna Savvana; Vani Mandava; Brian Dalessandro; Claudia Perlich; William Cukierski; Benjamin Hamner (IEEE BigData, 2013)

Scalable supervised dimensionality reduction using clustering. - Troy Raeder; Claudia Perlich; Brian Dalessandro; Ori Stitelman; Foster J. Provost (KDD, 2013)

The Microsoft academic search dataset and KDD Cup 2013. - Senjuti Basu Roy; Martine De Cock; Vani Mandava; Swapna Savanna; Brian Dalessandro; Claudia Perlich; William Cukierski; Ben Hamner (KDD Cup, 2013)

Using co-visitation networks for detecting large scale online display advertising exchange fraud. - Ori Stitelman; Claudia Perlich; Brian Dalessandro; Rod Hook; Troy Raeder; Foster J. Provost (KDD, 2013)

Scalable hands-free transfer learning for online advertising. - Brian Dalessandro; Daizhuo Chen; Troy Raeder; Claudia Perlich; Melinda Han Williams; Foster J. Provost (KDD, 2014)

Pleasing the advertising oracle: Probabilistic prediction from sampled, aggregated ground truth. - Melinda Han Williams; Claudia Perlich; Brian Dalessandro; Foster J. Provost (ADKDD@KDD, 2014)

Bigger is Better, but at What Cost?Estimating the Economic Value of Incremental Data Assets. - Brian Dalessandro; Claudia Perlich; Troy Raeder (Big Data, 2014)

A Data Scientist's Guide to Start-Ups. - Foster J. Provost; Geoffrey I. Webb; Ron Bekkerman; Oren Etzioni; Usama M. Fayyad; Claudia Perlich (Big Data, 2014)

Machine learning for targeted display advertising: transfer learning in action. - Claudia Perlich; Brian Dalessandro; Troy Raeder; Ori Stitelman; Foster J. Provost (Mach. Learn., 2014)

Evaluating and Optimizing Online Advertising: Forget the Click, but There Are Good Proxies. - Brian Dalessandro; Rod Hook; Claudia Perlich; Foster J. Provost (Big Data, 2015)

Automated Machine Learning in the Wild. - Claudia Perlich (RecSys, 2016)

Blacklisting the Blacklist in Online Advertising: Improving Delivery by Bidding for What You Can Win. - Yeming Shi; Ori Stitelman; Claudia Perlich (ADKDD@KDD, 2017)

Learning Curves in Machine Learning. - Claudia Perlich (Encyclopedia of Machine Learning and Data Mining, 2017)

Audience Size Forecasting: Fast and Smart Budget Planning for Media Buyers. - Yeming Shi; Claudia Perlich; Rod Hook; Wickus Martin; Melinda Han Williams; Justin Moynihan; Patrick McCarthy; Peter Lenz; Reka Daniel-Weiner; Roger Cost (KDD, 2018)

Beware of "Explanations" of AI. - David Martens; Galit Shmueli; Theodoros Evgeniou; Kevin Bauer; Christian Janiesch; Stefan Feuerriegel; Sebastian Gabel; Sofie Goethals; Travis Greene; Nadja Klein; Mathias Kraus; Niklas Kühl 001; et al. (CoRR, 2025)