Decoding by Linear Programming Emmanuel Candes† and Terence Tao] † Applied and Computational Mathematics, Caltech, Pasadena, CADepartment of Mathematics, University of California, Los Angeles, CADecem

Source URL: statweb.stanford.edu

Structured Output Layer with Auxiliary Targets for Context-Dependent Acoustic Modelling Pawel Swietojanski, Peter Bell, Steve Renals The Centre for Speech Technology Research, University of Edinburgh, United Kingdom {p.s

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

• Artificial neural networks
• Machine learning
• Computational neuroscience
• Applied mathematics
• Artificial intelligence
• Computational statistics
• Automatic identification and data capture
• Computer accessibility
• Speech recognition
• Language model
• Convolutional neural network
• Perceptron

Department  of  Applied  and  Computational     Mathematics  and  Statistics  Colloquium   Michael  Schweinberger   Department  of  Statistics   Rice  University  

Source URL: acms.nd.edu

Operator Upscaling for the Wave Equation Tetyana Vdovina Susan E. Minkoff (UMBC), Oksana Korostyshevskaya Department of Computational and Applied Mathematics Rice University, Houston TX

Source URL: trip.rice.edu

Multi-Scale Algorithm for Elliptic Equations

Source URL: www.ifd.mavt.ethz.ch

• Engineering
• Calculus
• Aerodynamics
• Mathematics
• Partial differential equations
• Chemical engineering
• Fluid dynamics
• Piping
• Fluid mechanics
• Equation
• Multigrid method
• Computational fluid dynamics

Evolution of Controllability in Interbank Networks SUBJECT AREAS: APPLIED MATHEMATICS APPLIED PHYSICS COMPUTATIONAL SCIENCE

Source URL: lims.ac.uk

Advances in Computational Mathematics) ?–? 1 Deficits and Excesses of Frames Radu Balan a , Peter G. Casazza b,∗ , Christopher Heil c,∗∗ , and Zeph Landau d

Source URL: www.math.umd.edu

arXiv:1409.3215v3 [cs.CL] 14 Dec 2014

Source URL: arxiv.org

• Artificial neural networks
• Artificial intelligence
• Machine learning
• Applied mathematics
• Computational linguistics
• Computational neuroscience
• Artificial intelligence applications
• Computer-assisted translation
• Deep learning
• Long short-term memory
• Recurrent neural network
• Speech recognition

Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? Emmanuel Candes† and Terence Tao] † Applied and Computational Mathematics, Caltech, Pasadena, CADepartment of Mathematics,

Source URL: statweb.stanford.edu

Frameworks for Modeling and Inversion William W. Symes The Rice Inversion Project Department of Computational and Applied Mathematics Rice University, Houston, TX

Source URL: trip.rice.edu