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ORCIDAutoML@ICML 2016: New York City, NY, USA
- Frank Hutter, Lars Kotthoff, Joaquin Vanschoren:
Proceedings of the 2016 Workshop on Automatic Machine Learning, AutoML 2016, co-located with 33rd International Conference on Machine Learning (ICML 2016), New York City, NY, USA, June 24, 2016. JMLR Workshop and Conference Proceedings 64, JMLR.org 2016
Accepted Papers
- Salisu Mamman Abdulrahman, Pavel Brazdil:
Effect of Incomplete Meta-dataset on Average Ranking Method. 1-10 - Ian Dewancker, Michael McCourt, Scott Clark, Patrick Hayes, Alexandra Johnson, George Ke:
A Strategy for Ranking Optimization Methods using Multiple Criteria. 11-20 - Isabelle Guyon, Imad Chaabane, Hugo Jair Escalante, Sergio Escalera, Damir Jajetic, James Robert Lloyd, Núria Macià, Bisakha Ray, Lukasz Romaszko, Michèle Sebag, Alexander R. Statnikov, Sébastien Treguer, Evelyne Viegas:
A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention. 21-30 - Hyunjik Kim, Yee Whye Teh:
Scalable Structure Discovery in Regression using Gaussian Processes. 31-40 - Gustavo Malkomes, Chip Schaff, Roman Garnett:
Bayesian optimization for automated model selection. 41-47 - Manuel Martin Salvador, Marcin Budka, Bogdan Gabrys:
Adapting Multicomponent Predictive Systems using Hybrid Adaptation Strategies with Auto-WEKA in Process Industry. 48-57 - Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Frank Hutter:
Towards Automatically-Tuned Neural Networks. 58-65 - Randal S. Olson, Jason H. Moore:
TPOT: A Tree-based Pipeline Optimization Tool for Automating Machine Learning. 66-74 - Francesco Orabona, Dávid Pál:
Parameter-Free Convex Learning through Coin Betting. 75-82
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