Ron Kohavi - RankMe

63 papers A* 28A 3B 3Journal 20Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Power Analysis is Essential: High-Powered Tests Suggest Minimal to No Effect of Rounded Shapes on Click-Through Rates. CoRR Ron Kohavi, Jakub Linowski, Lukas Vermeer, Fabrice Boisseranc, Joachim Furuseth, Andrew Gelman, Guido Imbens, Ravikiran Rajagopal
2024	A*	`conf`	False Positives in A/B Tests. KDD Ron Kohavi, Nanyu Chen
2022	A*	`conf`	A/B Testing Intuition Busters: Common Misunderstandings in Online Controlled Experiments. KDD Ron Kohavi, Alex Deng, Lukas Vermeer
2017	A*	`conf`	A/B Testing at Scale: Accelerating Software Innovation. SIGIR Alex Deng, Pavel A. Dmitriev, Somit Gupta, Ron Kohavi, Paul Raff, Lukas Vermeer
2017	—	`ch.`	Online Controlled Experiments and A/B Testing. Encyclopedia of Machine Learning and Data Mining Ron Kohavi, Roger Longbotham
2016	—	`conf`	Pitfalls of long-term online controlled experiments. IEEE BigData Pavel A. Dmitriev, Brian Frasca, Somit Gupta, Ron Kohavi, Garnet Jason Vaz
2015	A*	`conf`	Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 Years. KDD Ron Kohavi
2014	A*	`conf`	Seven rules of thumb for web site experimenters. KDD Ron Kohavi, Alex Deng, Roger Longbotham, Ya Xu
2013	A	`conf`	Improving the sensitivity of online controlled experiments by utilizing pre-experiment data. WSDM Alex Deng, Ya Xu, Ron Kohavi, Toby Walker
2013	A*	`conf`	Online controlled experiments at large scale. KDD Ron Kohavi, Alex Deng, Brian Frasca, Toby Walker, Ya Xu, Nils Pohlmann
2012	A	`conf`	Online controlled experiments: introduction, learnings, and humbling statistics. RecSys Ron Kohavi
2012	A*	`conf`	Trustworthy online controlled experiments: five puzzling outcomes explained. KDD Ron Kohavi, Alex Deng, Brian Frasca, Roger Longbotham, Toby Walker, Ya Xu
2010	J	`jnl`	Online Experiments: Practical Lessons. Computer Ron Kohavi, Roger Longbotham, Toby Walker
2010	J	`jnl`	Unexpected results in online controlled experiments. SIGKDD Explor. Ron Kohavi, Roger Longbotham
2009	J	`jnl`	Controlled experiments on the web: survey and practical guide. Data Min. Knowl. Discov. Ron Kohavi, Roger Longbotham, Dan Sommerfield, Randal M. Henne
2009	A*	`conf`	Seven pitfalls to avoid when running controlled experiments on the web. KDD Thomas Crook, Brian Frasca, Ron Kohavi, Roger Longbotham
2007	J	`jnl`	Online Experiments: Lessons Learned. Computer Ron Kohavi, Roger Longbotham
2007	A*	`conf`	Practical guide to controlled experiments on the web: listen to your customers not to the hippo. KDD Ron Kohavi, Randal M. Henne, Dan Sommerfield
2005	—	`conf`	Focus the Mining Beacon: Lessons and Challenges from the World of E-Commerce. PKDD Ron Kohavi
2004	J	`jnl`	Lessons and Challenges from Mining Retail E-Commerce Data. Mach. Learn. Ron Kohavi, Llew Mason, Rajesh Parekh, Zijian Zheng
2004	A*	`ed.`	Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, Washington, USA, August 22-25, 2004 KDD Won Kim, Ron Kohavi, Johannes Gehrke, William DuMouchel
2004	A	`conf`	Visualizing RFM Segmentation. SDM Ron Kohavi, Rajesh Parekh
2002	J	`jnl`	Emerging trends in business analytics. Commun. ACM Ron Kohavi, Neal Rothleder, Evangelos Simoudis
2002	—	`ed.`	WEBKDD 2001 - Mining Web Log Data Across All Customers Touch Points, Third International Workshop, San Francisco, CA, USA, August 26, 2001, Revised Papers WebKDD Ron Kohavi, Brij M. Masand, Myra Spiliopoulou, Jaideep Srivastava
2002	J	`jnl`	Web Mining. Data Min. Knowl. Discov. Ron Kohavi, Brij M. Masand, Myra Spiliopoulou, Jaideep Srivastava
2001	J	`jnl`	Applications of Data Mining to Electronic Commerce. Data Min. Knowl. Discov. Ron Kohavi, Foster J. Provost
2001	A*	`conf`	Integrating E-Commerce and Data Mining: Architecture and Challenges. ICDM Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng
2001	B	`conf`	Mining E-Commerce Data: The Good, the Bad, and the Ugly. PAKDD Ron Kohavi
2001	A*	`conf`	Mining e-commerce data: the good, the bad, and the ugly. KDD Ron Kohavi
2001	A*	`conf`	Real world performance of association rule algorithms. KDD Zijian Zheng, Ron Kohavi, Llew Mason
2000	J	`jnl`	Applications of Data Mining to Electronic Commerce CoRR Ron Kohavi, Foster J. Provost
2000	J	`jnl`	Integrating Data Mining into Vertical Solutions. SIGKDD Explor. Ron Kohavi, Mehran Sahami
2000	J	`jnl`	Integrating E-Commerce and Data Mining: Architecture and Challenges CoRR Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng
2000	J	`jnl`	KDD-Cup 2000 Organizers' Report: Peeling the Onion. SIGKDD Explor. Ron Kohavi, Carla E. Brodley, Brian Frasca, Llew Mason, Zijian Zheng
2000	J	`jnl`	WEBKDD 2000 - Web Mining for E-Commerce. SIGKDD Explor. Myra Spiliopoulou, Jaideep Srivastava, Ron Kohavi, Brij M. Masand
2000	A*	`conf`	Web mining for e-commerce (workshop session - title only). KDD Ron Kohavi, Myra Spiliopoulou, Jaideep Srivastava
1999	J	`jnl`	An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants. Mach. Learn. Eric Bauer, Ron Kohavi
1998	J	`jnl`	Guest Editors' Introduction: On Applied Research in Machine Learning. Mach. Learn. Foster J. Provost, Ron Kohavi
1998	—	`conf`	Pruning Decision Trees with Misclassification Costs. ECML Jeffrey P. Bradford, Clayton Kunz, Ron Kohavi, Clifford Brunk, Carla E. Brodley
1998	A*	`conf`	Targeting Business Users with Decision Table Classifiers. KDD Ron Kohavi, Dan Sommerfield
1998	A*	`conf`	The Case against Accuracy Estimation for Comparing Induction Algorithms. ICML Foster J. Provost, Tom Fawcett, Ron Kohavi
1997	J	`jnl`	Data Mining Using Int. J. Artif. Intell. Tools Ron Kohavi, Dan Sommerfield, James Dougherty
1997	A*	`conf`	MineSet: An Integrated System for Data Mining. KDD Clifford Brunk, James Kelly, Ron Kohavi
1997	A*	`conf`	Option Decision Trees with Majority Votes. ICML Ron Kohavi, Clayton Kunz
1997	J	`jnl`	Wrappers for Feature Subset Selection. Artif. Intell. Ron Kohavi, George H. John
1996	A*	`conf`	Bias Plus Variance Decomposition for Zero-One Loss Functions. ICML Ron Kohavi, David H. Wolpert
1996	J	`jnl`	Book Review: Empirical Methods for Artificial Intelligence. Int. J. Neural Syst. Ron Kohavi
1996	B	`conf`	Data Mining Using MLC++: A Machine Learning Library in C++. ICTAI Ron Kohavi, Dan Sommerfield, James Dougherty
1996	A*	`conf`	Error-Based and Entropy-Based Discretization of Continuous Features. KDD Ron Kohavi, Mehran Sahami
1996	—	`conf`	Lazy Decision Trees. AAAI/IAAI, Vol. 1 Jerome H. Friedman, Ron Kohavi, Yeogirl Yun
1996	A*	`conf`	Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. KDD Ron Kohavi
1995	A*	`conf`	A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. IJCAI Ron Kohavi
1995	A*	`conf`	Automatic Parameter Selection by Minimizing Estimated Error. ICML Ron Kohavi, George H. John
1995	A*	`conf`	Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology. KDD Ron Kohavi, Dan Sommerfield
1995	A*	`conf`	Oblivious Decision Trees, Graphs, and Top-Down Pruning. IJCAI Ron Kohavi, Chia-Hsin Li
1995	A*	`conf`	Supervised and Unsupervised Discretization of Continuous Features. ICML James Dougherty, Ron Kohavi, Mehran Sahami
1995	—	`conf`	The Power of Decision Tables. ECML Ron Kohavi
1995	—	`—`	Wrappers for performance enhancement and oblivious decision graphs. Ron Kohavi
1994	—	`conf`	Bottom-Up Induction of Oblivious Read-Once Decision Graphs. ECML Ron Kohavi
1994	A*	`conf`	Bottom-Up Induction of Oblivious Read-Once Decision Graphs: Strengths and Limitations. AAAI Ron Kohavi
1994	A*	`conf`	Irrelevant Features and the Subset Selection Problem. ICML George H. John, Ron Kohavi, Karl Pfleger
1994	B	`conf`	MLC++: A Machine Learning Library in C++. ICTAI Ron Kohavi, George H. John, Richard Long, David Manley, Karl Pfleger
1993	J	`jnl`	Research Note on Decision Lists. Mach. Learn. Ron Kohavi, Scott Benson