Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System Pradap Konda1 , Arun Kumar1 , Christopher Re´ 2 , Vaishnavi Sashikanth3 1 Department of Computer Sciences, University of

Source URL: cs.stanford.edu

• Data
• Humanities
• Computing
• Big data
• Business intelligence
• Cybernetics
• Learning
• Machine learning
• Provenance
• Analytics
• Oracle Database
• Geographic information system

UNSUPERVISED NEURAL NETWORK BASED FEATURE EXTRACTION USING WEAK TOP-DOWN CONSTRAINTS Herman Kamper1,2 , Micha Elsner3 , Aren Jansen4 , Sharon Goldwater2 1 CSTR and 2 ILCC, School of Informatics, University of Edinburgh,

Source URL: www.cstr.ed.ac.uk

• Machine learning
• Artificial neural networks
• Artificial intelligence
• Learning
• Applied mathematics
• Computational neuroscience
• Cybernetics
• Computational statistics
• Autoencoder
• Speech recognition
• Backpropagation
• Supervised learning

R ESEA R C H FEATURE Using Machine-Learning Methods for Musical Style Modeling Research using statistical and information-theoretic tools provides

Source URL: bejerano.stanford.edu

Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation Kyunghyun Cho Bart van Merri¨enboer Caglar Gulcehre Universit´e de Montr´eal

Source URL: arxiv.org

• Artificial neural networks
• Artificial intelligence
• Machine learning
• Applied mathematics
• Deep learning
• Recurrent neural network
• Recursive neural network
• Feature learning
• Word embedding
• Statistical machine translation
• Language model
• Autoencoder

TPAMI SPECIAL ISSUE SUBMISSION UNDER REVIEW 1 Scaling up Spike-and-Slab Models for Unsupervised Feature Learning

Source URL: www-etud.iro.umontreal.ca

ROBERTO BATTITI, MAURO BRUNATO. The LION Way: Machine Learning plus Intelligent Optimization. LIONlab, University of Trento, Italy, Apr 2015 http://intelligentoptimization.org/LIONbook

Source URL: intelligent-optimization.org

• Machine learning
• Model selection
• Learning
• Dimension reduction
• Feature selection
• Pattern recognition
• Roberto Battiti
• Feature
• Dimensionality reduction

arXiv:1406.1833v2 [cs.NE] 10 JunUnsupervised Feature Learning through Divergent Discriminative Feature Accumulation Paul A. Szerlip, Gregory Morse, Justin K. Pugh, and Kenneth O. Stanley Department EECS (Computer

Source URL: eplex.cs.ucf.edu

• Artificial neural networks
• Artificial intelligence
• Machine learning
• Learning
• Applied mathematics
• Evolutionary algorithms
• Computational neuroscience
• Evolutionary computation
• Neuroevolution
• Deep learning
• HyperNEAT
• Feature learning

Girl Scout Music Videos Great to help girls learn some classic Girl Scout songs! Make New Friends http://www.youtube.com/watch?v=E5ZmDA7nN-I&feature=related Brownie Smile song http://www.youtube.com/watch?v=9lcpeM-KiDE&f

Source URL: online.girlscoutsp2p-learning.org

arXiv:1502.04623v2 [cs.CV] 20 MayDRAW: A Recurrent Neural Network For Image Generation Karol Gregor Ivo Danihelka

Source URL: arxiv.org

• Artificial neural networks
• Artificial intelligence
• Computational neuroscience
• Cybernetics
• Applied mathematics
• Computational statistics
• Deep learning
• Machine learning
• Convolutional neural network
• Feature learning
• Recurrent neural network
• MNIST database

IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events ACOUSTIC SCENE CLASSIFICATION USING SPARSE FEATURE LEARNING AND SELECTIVE MAX-POOLING BY EVENT DETECTION Juhan Nam∗

Source URL: c4dm.eecs.qmul.ac.uk