Ron Kohavi

According to our database, Ron Kohavi authored at least 61 papers between 1993 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

A/B Testing Intuition Busters: Common Misunderstandings in Online Controlled Experiments.

Ron Kohavi, Alex Deng, Lukas Vermeer

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

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 at Scale: Accelerating Software Innovation.

Somit Gupta, Ronny Kohavi, Alex Deng, Jeff Omhover, Pawel Janowski

Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

2017

Online Controlled Experiments and A/B Testing.

Ron Kohavi, Roger Longbotham

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

A/B Testing at Scale: Accelerating Software Innovation.

Alex Deng, Pavel A. Dmitriev, Somit Gupta, Ron Kohavi, Paul Raff, Lukas Vermeer

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017

2016

Pitfalls of long-term online controlled experiments.

Pavel A. Dmitriev, Brian Frasca, Somit Gupta, Ron Kohavi, Garnet Jason Vaz

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 Years.

Ron Kohavi

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

Seven rules of thumb for web site experimenters.

Ron Kohavi, Alex Deng, Roger Longbotham, Ya Xu

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013

Improving the sensitivity of online controlled experiments by utilizing pre-experiment data.

Alex Deng, Ya Xu, Ron Kohavi, Toby Walker

Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

Online controlled experiments at large scale.

Ron Kohavi, Alex Deng, Brian Frasca, Toby Walker, Ya Xu, Nils Pohlmann

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Online controlled experiments: introduction, insights, scaling, and humbling statistics.

Ronny Kohavi

Proceedings of the 1st workshop on User engagement optimization, 2013

2012

Online controlled experiments: introduction, learnings, and humbling statistics.

Ron Kohavi

Proceedings of the Sixth ACM Conference on Recommender Systems, 2012

Trustworthy online controlled experiments: five puzzling outcomes explained.

Ron Kohavi, Alex Deng, Brian Frasca, Roger Longbotham, Toby Walker, Ya Xu

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

2010

Unexpected results in online controlled experiments.

Ron Kohavi, Roger Longbotham

SIGKDD Explor., 2010

Online Experiments: Practical Lessons.

Ron Kohavi, Roger Longbotham, Toby Walker

Computer, 2010

2009

Controlled experiments on the web: survey and practical guide.

Ron Kohavi, Roger Longbotham, Dan Sommerfield, Randal M. Henne

Data Min. Knowl. Discov., 2009

Seven pitfalls to avoid when running controlled experiments on the web.

Thomas Crook, Brian Frasca, Ron Kohavi, Roger Longbotham

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

2007

Online Experiments: Lessons Learned.

Ron Kohavi, Roger Longbotham

Computer, 2007

Practical guide to controlled experiments on the web: listen to your customers not to the hippo.

Ron Kohavi, Randal M. Henne, Dan Sommerfield

Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

2005

Focus the Mining Beacon: Lessons and Challenges from the World of E-Commerce.

Ron Kohavi

Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

2004

Lessons and Challenges from Mining Retail E-Commerce Data.

Ron Kohavi, Llew Mason, Rajesh Parekh, Zijian Zheng

Mach. Learn., 2004

Visualizing RFM Segmentation.

Ron Kohavi, Rajesh Parekh

Proceedings of the Fourth SIAM International Conference on Data Mining, 2004

2002

Web Mining.

Ron Kohavi, Brij M. Masand, Myra Spiliopoulou, Jaideep Srivastava

Data Min. Knowl. Discov., 2002

Emerging trends in business analytics.

Ron Kohavi, Neal Rothleder, Evangelos Simoudis

Commun. ACM, 2002

2001

Applications of Data Mining to Electronic Commerce.

Ron Kohavi, Foster J. Provost

Data Min. Knowl. Discov., 2001

Real world performance of association rule algorithms.

Zijian Zheng, Ron Kohavi, Llew Mason

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001

Mining e-commerce data: the good, the bad, and the ugly.

Ron Kohavi

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001

Integrating E-Commerce and Data Mining: Architecture and Challenges.

Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng

Proceedings of the 2001 IEEE International Conference on Data Mining, 29 November, 2001

2000

WEBKDD 2000 - Web Mining for E-Commerce.

Myra Spiliopoulou, Jaideep Srivastava, Ron Kohavi, Brij M. Masand

SIGKDD Explor., 2000

Integrating Data Mining into Vertical Solutions.

Ron Kohavi, Mehran Sahami

SIGKDD Explor., 2000

KDD-Cup 2000 Organizers' Report: Peeling the Onion.

Ron Kohavi, Carla E. Brodley, Brian Frasca, Llew Mason, Zijian Zheng

SIGKDD Explor., 2000

Web mining for e-commerce (workshop session - title only).

Ron Kohavi, Myra Spiliopoulou, Jaideep Srivastava

Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

1999

An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants.

Eric Bauer, Ron Kohavi

Mach. Learn., 1999

1998

Guest Editors' Introduction: On Applied Research in Machine Learning.

Foster J. Provost, Ron Kohavi

Mach. Learn., 1998

Targeting Business Users with Decision Table Classifiers.

Ron Kohavi, Dan Sommerfield

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

The Case against Accuracy Estimation for Comparing Induction Algorithms.

Foster J. Provost, Tom Fawcett, Ron Kohavi

Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

Pruning Decision Trees with Misclassification Costs.

Jeffrey P. Bradford, Clayton Kunz, Ron Kohavi, Clifford Brunk, Carla E. Brodley

Proceedings of the Machine Learning: ECML-98, 1998

1997

Data Mining Using <i>MLC</i> a Machine Learning Library in C++.

Ron Kohavi, Dan Sommerfield, James Dougherty

Int. J. Artif. Intell. Tools, 1997

Wrappers for Feature Subset Selection.

Ron Kohavi, George H. John

Artif. Intell., 1997

MineSet: An Integrated System for Data Mining.

Clifford Brunk, James Kelly, Ron Kohavi

Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

Option Decision Trees with Majority Votes.

Ron Kohavi, Clayton Kunz

Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1996

Census Income.

Ron Kohavi

Dataset, April, 1996

Adult.

Barry G. Becker, Ronny Kohavi

Dataset, April, 1996

Book Review: Empirical Methods for Artificial Intelligence.

Ron Kohavi

Int. J. Neural Syst., 1996

Error-Based and Entropy-Based Discretization of Continuous Features.

Ron Kohavi, Mehran Sahami

Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid.

Ron Kohavi

Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

Data Mining Using MLC++: A Machine Learning Library in C++.

Ron Kohavi, Dan Sommerfield, James Dougherty

Proceedings of the Eigth International Conference on Tools with Artificial Intelligence, 1996

Bias Plus Variance Decomposition for Zero-One Loss Functions.

Ron Kohavi, David H. Wolpert

Proceedings of the Machine Learning, 1996

Lazy Decision Trees.

Jerome H. Friedman, Ron Kohavi, Yeogirl Yun

Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1995

Wrappers for performance enhancement and oblivious decision graphs.

Ron Kohavi

PhD thesis, 1995

Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology.

Ron Kohavi, Dan Sommerfield

Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995

Oblivious Decision Trees, Graphs, and Top-Down Pruning.

Ron Kohavi, Chia-Hsin Li

Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection.

Ron Kohavi

Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

Automatic Parameter Selection by Minimizing Estimated Error.

Ron Kohavi, George H. John

Proceedings of the Machine Learning, 1995

Supervised and Unsupervised Discretization of Continuous Features.

James Dougherty, Ron Kohavi, Mehran Sahami

Proceedings of the Machine Learning, 1995

The Power of Decision Tables.

Ron Kohavi

Proceedings of the Machine Learning: ECML-95, 1995

1994

MLC++: A Machine Learning Library in C++.

Ron Kohavi, George H. John, Richard Long, David Manley, Karl Pfleger

Proceedings of the Sixth International Conference on Tools with Artificial Intelligence, 1994

Irrelevant Features and the Subset Selection Problem.

George H. John, Ron Kohavi, Karl Pfleger

Proceedings of the Machine Learning, 1994

Bottom-Up Induction of Oblivious Read-Once Decision Graphs.

Ron Kohavi

Proceedings of the Machine Learning: ECML-94, 1994

Bottom-Up Induction of Oblivious Read-Once Decision Graphs: Strengths and Limitations.

Ron Kohavi

Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994

1993

Research Note on Decision Lists.

Ron Kohavi, Scott Benson

Mach. Learn., 1993