Gradient boosting

Results: 83



#Item
21Ensemble learning / Gradient boosting / Gradient descent / AdaBoost / Gradient / BFGS method / Numerical analysis / Mathematical analysis / Mathematics

/home/tgd/s/ashenfelter/ml2004/tech-report/paper.dvi

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Source URL: www.cs.iastate.edu

Language: English - Date: 2004-09-12 22:29:55
22Statistical classification / Ensemble learning / Evaluation methods / Research methods / Support vector machine / Qualitative research / Feature selection / Gradient boosting / Statistics / Machine learning / Science

Stacked Generalization Learning to Analyze Teenage Distress

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Source URL: affect.media.mit.edu

Language: English - Date: 2015-03-14 18:32:13
23Ensemble learning / Decision trees / Statistical classification / Model selection / Linear classifier / Gradient boosting / Pay per click / Feature selection / Boosting / Machine learning / Statistics / Artificial intelligence

Practical Lessons from Predicting Clicks on Ads at Facebook Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu∗, Tao Xu∗, Yanxin Shi∗, Antoine Atallah∗, Ralf Herbrich∗, Stuart Bowers, Joaquin Quiñonero Candel

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Source URL: quinonero.net

Language: English - Date: 2014-09-14 16:43:06
24Econometrics / Decision trees / Ensemble learning / Supervised learning / Regularization / Gradient boosting / Linear regression / Logistic regression / Random forest / Statistics / Regression analysis / Machine learning

Introduction to Boosted Trees Tianqi Chen Oct Outline • Review of key concepts of supervised learning

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Source URL: homes.cs.washington.edu

Language: English - Date: 2015-05-06 23:13:25
25Cross-validation / Poisson regression / Pattern recognition / Feature selection / Least squares / Regression analysis / Regularization / Gradient boosting / Book:Machine Learning - The Complete Guide / Statistics / Machine learning / Supervised learning

Ad Click Prediction: a View from the Trenches H. Brendan McMahan, Gary Holt, D. Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lan Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, Sharat Chikkerur, Dan Liu, Mart

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Source URL: static.googleusercontent.com

Language: English - Date: 2013-08-12 13:25:40
26Convex optimization / Machine learning / Operations research / Information retrieval / Learning to rank / Gradient boosting / Lagrange multiplier / Supervised learning / Interior point method / Mathematical optimization / Numerical analysis / Mathematical analysis

IntervalRank — Isotonic Regression with Listwise and Pairwise Constraints ∗ Taesup Moon, Alex Smola , Yi Chang, Zhaohui Zheng Yahoo! Labs

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Source URL: www.wsdm-conference.org

Language: English - Date: 2009-12-30 01:26:32
27Machine learning / Operations research / Information retrieval / Learning to rank / Convex optimization / Supervised learning / Gradient boosting / Lagrange multiplier / BFGS method / Mathematical optimization / Mathematics / Mathematical analysis

IntervalRank — Isotonic Regression with Listwise and Pairwise Constraints ∗ Taesup Moon, Alex Smola , Yi Chang, Zhaohui Zheng Yahoo! Labs

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Source URL: www.yichang-cs.com

Language: English - Date: 2009-11-15 16:54:36
28Additive model / Boosting / Least squares / Quantile regression / Gradient boosting / Statistics / Regression analysis / Logistic regression

Journal of Machine Learning Research[removed]2113 Submitted 2/10; Revised 4/10; Published 8/10 Model-based Boosting 2.0 Torsten Hothorn

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Source URL: www.jmlr.org

Language: English - Date: 2010-08-18 16:38:50
29Learning / Computational neuroscience / Ensemble learning / Cybernetics / Learning to rank / Gradient boosting / Support vector machine / Neural network / Ranking function / Machine learning / Statistics / Artificial intelligence

Multi-Task Learning for Learning to Rank in Web Search Jing Bai Ke Zhou, Guirong Xue Yahoo! Labs

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Source URL: www.yichang-cs.com

Language: English - Date: 2009-11-16 16:18:36
30Learning to rank / Artificial intelligence / Science / Discounted cumulative gain / Mathematical optimization / Gradient boosting / Gradient descent / Ranking function / Information science / Machine learning / Information retrieval

Smoothing DCG for Learning to Rank: A Novel Approach Using Smoothed Hinge Functions Mingrui Wu, Yi Chang, Zhaohui Zheng Web Search Ranking Group, Yahoo! Labs, 701 First Avenue, Sunnyvale, CA 94089

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Source URL: www.yichang-cs.com

Language: English - Date: 2009-11-16 16:19:12
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