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Search Results for 'Data Kernels'

Data Kernels published presentations and documents on DocSlides.

Introduction to Kernels

Introduction to Kernels

  • lindy-dunigan
  • 43 Slides

April 2016. Agenda. Overview. Kernel architecture...

“Comments” In SPICE Kernels

“Comments” In SPICE Kernels

  • pamella-moone
  • 17 Slides

Also known as “meta-data”. April 2016. Commen...

Porting Kernels

Porting Kernels

  • liane-varnes
  • 19 Slides

April 2016. Porting Kernels. 2. Porting Issues - ...

Kernels and

Kernels and

  • pamella-moone
  • 42 Slides

Perceptrons. The . perceptron. A. B. instance. ....

Distributed Tree Kernels

Distributed Tree Kernels

  • debby-jeon
  • 0 Slides

and . Distributional. Semantics. :. Between. ....

Support Vector Machines and Kernel Methods

Support Vector Machines and Kernel Methods

  • pasty-toler
  • 39 Slides

Machine Learning. March 25, 2010. Last Time. Basi...

Support Vector Machines and Kernel Methods

Support Vector Machines and Kernel Methods

  • pasty-toler
  • 24 Slides

Machine Learning. March 25, 2010. Last Time. Reca...

Orchestrating Multiple Data-Parallel Kernels on Multiple De

Orchestrating Multiple Data-Parallel Kernels on Multiple De

  • faustina-dinatale
  • 26 Slides

Janghaeng Lee. , . Mehrzad. . Samadi. , and Scot...

On Multiple Kernel Learning

On Multiple Kernel Learning

  • lindy-dunigan
  • 22 Slides

with Multiple Labels. Lei Tang. , . Jianhui. Che...

Reflected

Reflected

  • cheryl-pisano
  • 33 Slides

Solar . Radiative. Kernel. s. And Applications...

Histograms of Oriented Optical Flow and BinetCauchy Kernels on Nonlinear Dynamical Systems for the Recognition of Human Actions Rizwan Chaudhry Avinash Ravichandran Gregory Hager and Ren e Vidal Cent

Histograms of Oriented Optical Flow and BinetCauchy Kernels on Nonlinear Dynamical Systems for the Recognition of Human Actions Rizwan Chaudhry Avinash Ravichandran Gregory Hager and Ren e Vidal Cent

  • celsa-spraggs
  • 8 Slides

g BinetCauchy kernels However such approaches are...

Hybrid maize breeding with doub led haploid lines quan

Hybrid maize breeding with doub led haploid lines quan

  • tatiana-dople
  • 14 Slides

ij DD ij ij ij ij ij DD DD DD brPage 4br DD ii TA...

UNECE

UNECE

  • yoshiko-marsland
  • 32 Slides

Brochure . for Walnuts . Photos . 7 April 2014. A...

Ed Nightingale, Orion Hodson,

Ed Nightingale, Orion Hodson,

  • kittie-lecroy
  • 26 Slides

Ross McIlroy, Chris Hawblitzel, Galen Hunt. Micro...

Fast & Flexible High-Level

Fast & Flexible High-Level

  • natalia-silvester
  • 23 Slides

S. ynthesis from . OpenCL. using Reconfiguration...

By. Tiffany Richard

By. Tiffany Richard

  • celsa-spraggs
  • 15 Slides

Popcorn project. Problem. What brand of microwave...

Features, Formalized

Features, Formalized

  • myesha-ticknor
  • 51 Slides

Stephen Mayhew. Hyung Sul Kim. 1. Outline. What a...

Warped-Slicer:

Warped-Slicer:

  • alida-meadow
  • 36 Slides

. Efficient Intra-SM Slicing through Dynamic Res...

Generalization and

Generalization and

  • pasty-toler
  • 50 Slides

Specialization of Kernelization. Daniel Lokshtano...

Automatically Exploiting Implicit

Automatically Exploiting Implicit

  • debby-jeon
  • 21 Slides

Pipeline . Parallelism from . Multiple . Dependen...

DCompute

DCompute

  • test
  • 28 Slides

:. Native & Convenient Heterogeneous. Computi...

Statistical Models and Methods

Statistical Models and Methods

  • pamella-moone
  • 0 Slides

for Computer Experiments. Habilitation . à. . D...

Deep Learning for Dense Geometric Correspondence Problems

Deep Learning for Dense Geometric Correspondence Problems

  • alida-meadow
  • 0 Slides

Ke Wang. Sparse Correspondence Problems. Dense Co...

Fluidic Kernels: Cooperative Execution of

Fluidic Kernels: Cooperative Execution of

  • pasty-toler
  • 47 Slides

OpenCL. Programs on Multiple Heterogeneous Devic...

Kernel Methods

Kernel Methods

  • luanne-stotts
  • 24 Slides

A B M Shawkat Ali. 1. 2. Data Mining. ¤. . DM ...

Employing compression solutions under

Employing compression solutions under

  • tawny-fly
  • 32 Slides

openacc. Ebad. . Salehi. , Ahmad . Lashgar. and...

Popcorn Lab Purpose : To further understand (more independently) how to solve scientific problems t

Popcorn Lab Purpose : To further understand (more independently) how to solve scientific problems t

  • ellena-manuel
  • 0 Slides

Popcorn Lab. Have you ever wondered why the delic...

Extensible Distributed Tracing from Kernels to Clusters

Extensible Distributed Tracing from Kernels to Clusters

  • jane-oiler
  • 30 Slides

Úlfar Erlingsson, Google Inc.. Marcus . Peinado....

FAT-GPU: Formal Analysis Techniques for GPU Kernels

FAT-GPU: Formal Analysis Techniques for GPU Kernels

  • marina-yarberry
  • 72 Slides

Alastair Donaldson. Imperial College London. www....

GPU Computing with

GPU Computing with

  • giovanna-bartolotta
  • 49 Slides

OpenACC. Directives. subroutine . saxpy. (n, a, ...

Extensible Distributed Tracing from Kernels to Clusters

Extensible Distributed Tracing from Kernels to Clusters

  • ellena-manuel
  • 39 Slides

Úlfar Erlingsson, Google Inc.. Marcus . Peinado....

Mascar

Mascar

  • debby-jeon
  • 19 Slides

: Speeding up GPU Warps . by . Reducing Memory . ...

Why do non-Mendelian

Why do non-Mendelian

  • calandra-battersby
  • 13 Slides

patterns . occur?. (When to decide whether it is ...

OpenCL Introduction Open standard for parallel programming across

OpenCL Introduction Open standard for parallel programming across

  • pasty-toler
  • 0 Slides

heterogenous. devices. Devices can consist of CP...

Journal of Machine Learning Research Submitted Published Text Classication using String Kernels Huma Lodhi humacs

Journal of Machine Learning Research Submitted Published Text Classication using String Kernels Huma Lodhi humacs

  • tatyana-admore
  • 26 Slides

rhulacuk Craig Saunders craigcsrhulacuk John Shawe...

Filter Forests for Learning DataDependent Convolutional Kernels Sean Ryan Fanello Cem Keskin Pushmeet Kohli Shahram Izadi Jamie Shotton Antonio Criminisi Ugo Pattacini Tim Paek Microsoft Research iC

Filter Forests for Learning DataDependent Convolutional Kernels Sean Ryan Fanello Cem Keskin Pushmeet Kohli Shahram Izadi Jamie Shotton Antonio Criminisi Ugo Pattacini Tim Paek Microsoft Research iC

  • liane-varnes
  • 8 Slides

FF can be used for general signal restoration tas...

Convolution Kernels for Natural Language Michael Collins ATT LabsResearch Park Avenue New Jersey NJ mcollinsresearch

Convolution Kernels for Natural Language Michael Collins ATT LabsResearch Park Avenue New Jersey NJ mcollinsresearch

  • alexa-scheidler
  • 8 Slides

attcom Nigel Duffy Department of Computer Science ...

Supervised Hashing with Kernels Wei Liu Jun Wang Rongrong Ji YuGang Jiang ShihFu Chang Electrical Engineering Department Columbia University New York NY USA IBM T

Supervised Hashing with Kernels Wei Liu Jun Wang Rongrong Ji YuGang Jiang ShihFu Chang Electrical Engineering Department Columbia University New York NY USA IBM T

  • celsa-spraggs
  • 8 Slides

J Watson Research Center Yorktown Heights NY USA ...

FineGrained Resource Sharing for Concurrent GPGPU Kernels Chris Gregg Jonathan Dorn Kim Hazelwood Kevin Skadron Department of Computer Science University of Virginia PO Box Charlottesville VA ABSTR

FineGrained Resource Sharing for Concurrent GPGPU Kernels Chris Gregg Jonathan Dorn Kim Hazelwood Kevin Skadron Department of Computer Science University of Virginia PO Box Charlottesville VA ABSTR

  • kittie-lecroy
  • 6 Slides

However in some cases it is possible to utilize d...

Subgraph Matching Kernels for Attributed Graphs Nils K

Subgraph Matching Kernels for Attributed Graphs Nils K

  • stefany-barnette
  • 8 Slides

kriegecstudortmundde Petra Mutzel petramutzelcstud...

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