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Feature learning
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#	Item
231	Kalyan Veeramachaneni Computer Science and Artificial Intelligence Laboratory, 32-D540, MIT, Cambridge, MA 02139, USA, This version: January 8, 2016 Latest: www.kalyanv.org Add to Reading List Source URL: groups.csail.mit.edu Language: English - Date: 2016-01-08 02:34:58 Evolution Cybernetics Machine learning Association for Computing Machinery Genetic and Evolutionary Computation Conference Deep feature synthesis Evolutionary computation Data mining Evolutionary algorithm Computational intelligence Academia Computer science
232	Boos$ng on a Budget: Sampling for Feature-‐Eﬃcient Predic$on ICML 2011 Lev Reyzin Georgia Ins$tute of Technology Add to Reading List Source URL: www.levreyzin.com Language: English - Date: 2011-06-29 21:11:52 Ensemble learning AdaBoost Boosting
233	Deep Feature Synthesis: Towards Automating Data Science Endeavors James Max Kanter Kalyan Veeramachaneni Add to Reading List Source URL: groups.csail.mit.edu Language: English - Date: 2015-10-15 14:47:29 Machine learning Formal sciences Learning Artificial intelligence Statistics K-means clustering Pattern recognition Deep feature synthesis Deep learning Data mining Support vector machine Artificial neural network
234	Boosting Approaches to Learning on a Feature Budget 1 Add to Reading List Source URL: www.levreyzin.com Language: English - Date: 2014-07-15 14:29:17 Ensemble learning Machine learning Boosting AdaBoost Supervised learning Statistical classification Feature selection Ensembles of classifiers LPBoost
235	Local Convolutional Features with Unsupervised Training for Image Retrieval Mattis Paulin 1 Julien Mairal1 1 Inria ∗ Add to Reading List Source URL: www.cv-foundation.org Language: English - Date: 2015-10-24 14:55:25 Feature detection Computer vision Artificial intelligence Vision Computational neuroscience Convolutional neural network Deep learning Outline of object recognition Maximally stable extremal regions Visual descriptor GLOH Conference on Computer Vision and Pattern Recognition
236	Boosting on a Budget: Sampling for Feature-Efficient Prediction Lev Reyzin Georgia Institute of Technology, 266 Ferst Drive, Atlanta, GA 30332, USA Abstract Add to Reading List Source URL: www.levreyzin.com Language: English - Date: 2011-05-05 13:47:57 Machine learning Artificial intelligence Ensemble learning Learning AdaBoost Boosting Online machine learning Generalization error Decision stump Sampling Margin classifier CoBoosting
237	Scaling up Inverse Reinforcement Learning through Instructed Feature Construction Tomas Singliar Dragos D. Margineantu Boeing Research & Technology P.O. Box 3707, M/C 7L-44 Add to Reading List Source URL: snowbird.djvuzone.org Language: English - Date: 2011-02-10 16:50:25
238	Nonlinear Extensions of Reconstruction ICA Apaar Sadhwani and Apoorv Gupta CS229 Project Report, Fall 2011 Abstract— In a recent paper [1] it was observed that unsupervised feature learning with overcomplete features c Add to Reading List Source URL: cs229.stanford.edu Language: English - Date: 2012-01-24 22:54:15
239	IEEE PEM December 2014 Feature (Deepak Divan) -Power Electronics at the Grid Edge25-14) Add to Reading List Source URL: groups.csail.mit.edu Language: English - Date: 2015-02-05 11:22:32 Machine learning Artificial intelligence Learning Ensemble learning Cognition Random subspace method Supervised learning Statistical classification
240	Playing Atari with Deep Reinforcement Learning Volodymyr Mnih Koray Kavukcuoglu Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-12-19 20:23:45 Artificial intelligence Computational neuroscience Machine learning Learning Artificial neural networks Cybernetics Q-learning Reinforcement learning Deep learning Markov decision process Feature learning Temporal difference learning

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