Research Note on Decision Lists. - Ron Kohavi; Scott Benson (Mach. Learn., 1993)

Bottom-Up Induction of Oblivious Read-Once Decision Graphs: Strengths and Limitations. - Ron Kohavi (AAAI, 1994)

Bottom-Up Induction of Oblivious Read-Once Decision Graphs. - Ron Kohavi (ECML, 1994)

Irrelevant Features and the Subset Selection Problem. - George H. John; Ron Kohavi; Karl Pfleger (ICML, 1994)

MLC++: A Machine Learning Library in C++. - Ron Kohavi; George H. John; Richard Long; David Manley; Karl Pfleger (ICTAI, 1994)

The Power of Decision Tables. - Ron Kohavi (ECML, 1995)

Supervised and Unsupervised Discretization of Continuous Features. - James Dougherty; Ron Kohavi; Mehran Sahami (ICML, 1995)

Automatic Parameter Selection by Minimizing Estimated Error. - Ron Kohavi; George H. John (ICML, 1995)

A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. - Ron Kohavi (IJCAI, 1995)

Oblivious Decision Trees, Graphs, and Top-Down Pruning. - Ron Kohavi; Chia-Hsin Li (IJCAI, 1995)

Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology. - Ron Kohavi; Dan Sommerfield (KDD, 1995)

Wrappers for performance enhancement and oblivious decision graphs. - Ron Kohavi (1995)

Lazy Decision Trees. - Jerome H. Friedman; Ron Kohavi; Yeogirl Yun (AAAI/IAAI, Vol. 1, 1996)

Bias Plus Variance Decomposition for Zero-One Loss Functions. - Ron Kohavi; David H. Wolpert (ICML, 1996)

Data Mining Using MLC++: A Machine Learning Library in C++. - Ron Kohavi; Dan Sommerfield; James Dougherty (ICTAI, 1996)

Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. - Ron Kohavi (KDD, 1996)

Error-Based and Entropy-Based Discretization of Continuous Features. - Ron Kohavi; Mehran Sahami (KDD, 1996)

Book Review: Empirical Methods for Artificial Intelligence. - Ron Kohavi (Int. J. Neural Syst., 1996)

Adult. - Barry G. Becker; Ronny Kohavi (UCI Machine Learning Repository, 1996)

Census Income. - Ron Kohavi (UCI Machine Learning Repository, 1996)

Option Decision Trees with Majority Votes. - Ron Kohavi; Clayton Kunz (ICML, 1997)

MineSet: An Integrated System for Data Mining. - Clifford Brunk; James Kelly; Ron Kohavi (KDD, 1997)

Wrappers for Feature Subset Selection. - Ron Kohavi; George H. John (Artif. Intell., 1997)

Data Mining Using MLC a Machine Learning Library in C++. - Ron Kohavi; Dan Sommerfield; James Dougherty (Int. J. Artif. Intell. Tools, 1997)

Pruning Decision Trees with Misclassification Costs. - Jeffrey P. Bradford; Clayton Kunz; Ron Kohavi; Clifford Brunk; Carla E. Brodley (ECML, 1998)

The Case against Accuracy Estimation for Comparing Induction Algorithms. - Foster J. Provost; Tom Fawcett; Ron Kohavi (ICML, 1998)

Targeting Business Users with Decision Table Classifiers. - Ron Kohavi; Dan Sommerfield (KDD, 1998)

Guest Editors' Introduction: On Applied Research in Machine Learning. - Foster J. Provost; Ron Kohavi (Mach. Learn., 1998)

An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants. - Eric Bauer; Ron Kohavi (Mach. Learn., 1999)

Web mining for e-commerce (workshop session - title only). - Ron Kohavi; Myra Spiliopoulou; Jaideep Srivastava (KDD, 2000)

KDD-Cup 2000 Organizers' Report: Peeling the Onion. - Ron Kohavi; Carla E. Brodley; Brian Frasca; Llew Mason; Zijian Zheng 002 (SIGKDD Explor., 2000)

Integrating Data Mining into Vertical Solutions. - Ron Kohavi; Mehran Sahami (SIGKDD Explor., 2000)

WEBKDD 2000 - Web Mining for E-Commerce. - Myra Spiliopoulou; Jaideep Srivastava; Ron Kohavi; Brij M. Masand (SIGKDD Explor., 2000)

Integrating E-Commerce and Data Mining: Architecture and Challenges. - Suhail Ansari; Ron Kohavi; Llew Mason; Zijian Zheng 002 (ICDM, 2001)

Mining e-commerce data: the good, the bad, and the ugly. - Ron Kohavi (KDD, 2001)

Real world performance of association rule algorithms. - Zijian Zheng 002; Ron Kohavi; Llew Mason (KDD, 2001)

Applications of Data Mining to Electronic Commerce. - Ron Kohavi; Foster J. Provost (Data Min. Knowl. Discov., 2001)

Emerging trends in business analytics. - Ron Kohavi; Neal Rothleder; Evangelos Simoudis (Commun. ACM, 2002)

Web Mining. - Ron Kohavi; Brij M. Masand; Myra Spiliopoulou; Jaideep Srivastava (Data Min. Knowl. Discov., 2002)

Visualizing RFM Segmentation. - Ron Kohavi; Rajesh Parekh (SDM, 2004)

Lessons and Challenges from Mining Retail E-Commerce Data. - Ron Kohavi; Llew Mason; Rajesh Parekh; Zijian Zheng 002 (Mach. Learn., 2004)

Focus the Mining Beacon: Lessons and Challenges from the World of E-Commerce. - Ron Kohavi (PKDD, 2005)

Practical guide to controlled experiments on the web: listen to your customers not to the hippo. - Ron Kohavi; Randal M. Henne; Dan Sommerfield (KDD, 2007)

Online Experiments: Lessons Learned. - Ron Kohavi; Roger Longbotham (Computer, 2007)

Seven pitfalls to avoid when running controlled experiments on the web. - Thomas Crook; Brian Frasca; Ron Kohavi; Roger Longbotham (KDD, 2009)

Controlled experiments on the web: survey and practical guide. - Ron Kohavi; Roger Longbotham; Dan Sommerfield; Randal M. Henne (Data Min. Knowl. Discov., 2009)

Online Experiments: Practical Lessons. - Ron Kohavi; Roger Longbotham; Toby Walker (Computer, 2010)

Unexpected results in online controlled experiments. - Ron Kohavi; Roger Longbotham (SIGKDD Explor., 2010)

Trustworthy online controlled experiments: five puzzling outcomes explained. - Ron Kohavi; Alex Deng; Brian Frasca; Roger Longbotham; Toby Walker; Ya Xu (KDD, 2012)

Online controlled experiments: introduction, learnings, and humbling statistics. - Ron Kohavi (RecSys, 2012)

Online controlled experiments: introduction, insights, scaling, and humbling statistics. - Ronny Kohavi (UEO@CIKM, 2013)

Online controlled experiments at large scale. - Ron Kohavi; Alex Deng; Brian Frasca; Toby Walker; Ya Xu; Nils Pohlmann (KDD, 2013)

Improving the sensitivity of online controlled experiments by utilizing pre-experiment data. - Alex Deng; Ya Xu; Ron Kohavi; Toby Walker (WSDM, 2013)

Seven rules of thumb for web site experimenters. - Ron Kohavi; Alex Deng; Roger Longbotham; Ya Xu (KDD, 2014)

Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 Years. - Ron Kohavi (KDD, 2015)

Pitfalls of long-term online controlled experiments. - Pavel A. Dmitriev; Brian Frasca; Somit Gupta; Ron Kohavi; Garnet Jason Vaz (IEEE BigData, 2016)

A/B Testing at Scale: Accelerating Software Innovation. - Alex Deng; Pavel A. Dmitriev; Somit Gupta; Ron Kohavi; Paul Raff; Lukas Vermeer (SIGIR, 2017)

Online Controlled Experiments and A/B Testing. - Ron Kohavi; Roger Longbotham (Encyclopedia of Machine Learning and Data Mining, 2017)

A/B Testing at Scale: Accelerating Software Innovation. - Somit Gupta; Ronny Kohavi; Alex Deng; Jeff Omhover; Pawel Janowski (WWW (Companion Volume), 2019)

Top Challenges from the first Practical Online Controlled Experiments Summit. - Somit Gupta; Ronny Kohavi; Diane Tang; Ya Xu (SIGKDD Explor., 2019)

A/B Testing Intuition Busters: Common Misunderstandings in Online Controlled Experiments. - Ron Kohavi; Alex Deng; Lukas Vermeer (KDD, 2022)

False Positives in A/B Tests. - Ron Kohavi; Nanyu Chen (KDD, 2024)