Development and Performance of a Statistical-Dynamical Ensemble Technique for Tropical Cyclone Intensity Guidance Kate D. Musgrave1 and Mark DeMaria2 1CIRA/CSU,

Source URL: www.hfip.org

STATISTICAL POST-PROCESSING FOR HURRICANE ENSEMBLE FORECASTING Zoltan Toth, Roman Krzysztofowicz1, and Tom Hamill ESRL/OAR/NOAA 1 Univeristy

Source URL: www.hfip.org

Predictive Analytics Using Statistical, Learning, and Ensemble Methods to Support Real-Time Exploration of Discrete Event Simulations Walid Budgagaa , Matthew Malenseka , Sangmi Pallickaraa , Neil Harveyb , F. Jay Breidt

Source URL: galileo.cs.colostate.edu

2016 HEPEX Workshop, Quebec, Canada Ensemble for better hydrological forecasts Day 1: 6 June: Registration and coffee

Source URL: hepex.irstea.fr

• Prediction
• Physical geography
• Weather forecasting
• Academia
• Statistical forecasting
• Hydrology
• Climate modeling
• Flood forecasting
• Ensemble forecasting
• Forecast verification
• Numerical weather prediction
• National Weather Service

Efficient and Robust Automated Machine Learning Matthias Feurer Aaron Klein Katharina Eggensperger Jost Tobias Springenberg

Source URL: papers.nips.cc

• Artificial intelligence
• Statistics
• Machine learning
• Model selection
• Statistical classification
• Ensemble learning
• Hyperparameter optimization
• Mathematical optimization
• Support vector machine
• Boosting
• Deep learning
• Weka

presently done) or by simply delivering to the end user uncertain, and hardly understood, forecasts (as commonly planned to be done). This work also introduces and discusses the presently available continuous (Hydrologic

Source URL: hepex.irstea.fr

• Weather forecasting
• Prediction
• Meteorology
• Physical geography
• Statistical forecasting
• Climate modeling
• Hydrology
• Weather prediction
• Quantitative precipitation forecast
• Ensemble forecasting
• Numerical weather prediction
• European Centre for Medium-Range Weather Forecasts

A Few Useful Things to Know about Machine Learning Pedro Domingos Department of Computer Science and Engineering University of Washington Seattle, WA, U.S.A.

Source URL: homes.cs.washington.edu

• Machine learning
• Artificial intelligence
• Statistical classification
• Learning
• Ensemble learning
• Cybernetics
• Boosting
• Support vector machine
• Linear classifier
• Naive Bayes classifier
• Online machine learning
• Generalization error

Wildfire Season Forecast Dr. Kerry Anderson, Fire Research Scientist, Canadian Forest Service, Natural Resources Canada

Source URL: www.iclr.org

• Prediction
• Climate modeling
• Climatology
• Physical geography
• Statistical forecasting
• Weather forecasting
• Ensemble forecasting
• Atmospheric model
• Meteorology
• Forecasting
• Numerical weather prediction
• Quantitative precipitation forecast

Charu C. Aggarwal IBM T J Watson Research Center Yorktown, NYOutlier Ensembles

Source URL: www.outlier-analytics.org

• Statistics
• Information
• Data
• Data mining
• Robust statistics
• Outlier
• Statistical data
• Formal sciences
• Ensemble learning
• K-nearest neighbors algorithm
• Local outlier factor
• Anomaly detection

Methods for Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive Evaluation to Inform Decision Support System Development Alexander Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos Discovery S

Source URL: www.dsl-lab.org

• Machine learning
• Learning
• Statistics
• Artificial intelligence
• Statistical classification
• Model selection
• Support vector machine
• Cross-validation
• K-nearest neighbors algorithm
• Ensemble learning
• Kernel method
• Pattern recognition