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Data Analytics

Data Analytics

  • tatiana-dople
  • 64 Slides

(CS40003). Dr. Debasis Samanta. Associate Profess...

Machine Learning for Spam Filtering

Machine Learning for Spam Filtering

  • karlyn-bohler
  • 14 Slides

. 1. Sai Koushik Haddunoori. Problem:. E-mail p...

Pure Quotation and Natural Naming

Pure Quotation and Natural Naming

  • kittie-lecroy
  • 88 Slides

26 September 2016 – . Lingnan. University. Mic...

Minimum Redundancy and Maximum Relevance Feature Selection

Minimum Redundancy and Maximum Relevance Feature Selection

  • kittie-lecroy
  • 27 Slides

Hang Xiao. Background. Feature. a . feature. is ...

Cross Validation

Cross Validation

  • faustina-dinatale
  • 11 Slides

False Negatives / Negatives. ד"ר אבי רוז...

Automated Macular Pathology Diagnosis

Automated Macular Pathology Diagnosis

  • celsa-spraggs
  • 29 Slides

in Retinal OCT Images. . Using Multi-Scale Spati...

Sarcasm Detection on

Sarcasm Detection on

  • liane-varnes
  • 22 Slides

Twitter . A Behavioral Modeling . Approach. Ashwi...

An Introduction to Machine Learning

An Introduction to Machine Learning

  • pasty-toler
  • 49 Slides

Presented to LING-7800 . Shumin . Wu. Prepared by...

Interpolants

Interpolants

  • aaron
  • 23 Slides

as Classifiers. Rahul Sharma. Joint work with . ...

Efficient Logistic Regression with Stochastic Gradient Desc

Efficient Logistic Regression with Stochastic Gradient Desc

  • tatiana-dople
  • 34 Slides

William Cohen. 1. SGD for Logistic Regression. 2....

Spam Email Detection

Spam Email Detection

  • pasty-toler
  • 7 Slides

Ethan Grefe. December . 13, . 2013. Motivation. S...

CS 6501: Deep Learning

CS 6501: Deep Learning

  • mitsue-stanley
  • 85 Slides

for. Computer Graphics. Basics of Machine Learnin...

Twitter as a Corpus for Sentiment Analysis and Opinion Mini

Twitter as a Corpus for Sentiment Analysis and Opinion Mini

  • tatiana-dople
  • 21 Slides

Adam. Rosenberg, Leandra Irvine, Gus . Logsdon. ...

A Robust and Energy-Efficient Classifier

A Robust and Energy-Efficient Classifier

  • olivia-moreira
  • 17 Slides

Using Brain-Inspired . Hyperdimensional Computing...

Unsupervised Learning of Visual Sense Models for Polysemous

Unsupervised Learning of Visual Sense Models for Polysemous

  • tatyana-admore
  • 12 Slides

Kate Saenko Trevor Darrell. Deepak. Polysemy. Amb...

Nearly optimal classification for

Nearly optimal classification for

  • lois-ondreau
  • 28 Slides

semimetrics. Lee-Ad Gottlieb Ariel U.. Aryeh. ....

An Efficient GPGPU Implementation of

An Efficient GPGPU Implementation of

  • danika-pritchard
  • 43 Slides

Viola-Jones Classifier . based Face Detection Alg...

PyWBEM

PyWBEM

  • natalia-silvester
  • 28 Slides

Python WBEM Client: . Overview. Karl Schopmeyer....

Deep Learning Tutorial

Deep Learning Tutorial

  • phoebe-click
  • 109 Slides

李宏. 毅. Hung-yi Lee. Deep learning . attract...

Yuan

Yuan

  • tatyana-admore
  • 25 Slides

Zhou, . Ryan O’Donnell. Carnegie Mellon . Unive...

Classification based on Association Rules

Classification based on Association Rules

  • tatyana-admore
  • 5 Slides

Introduction. Association rules were originally d...

Shadi

Shadi

  • mitsue-stanley
  • 31 Slides

. Khalifa. Database Systems Laboratory (DSL). kh...

Boosting

Boosting

  • faustina-dinatale
  • 19 Slides

CMPUT 615. Boosting Idea. . We have a weak class...

Guest lecture II: Amos Fiat’s

Guest lecture II: Amos Fiat’s

  • min-jolicoeur
  • 60 Slides

Social Networks class . Edith Cohen. TAU, Decembe...

Heart Sound Biometrics for Continual User Authentication

Heart Sound Biometrics for Continual User Authentication

  • tawny-fly
  • 13 Slides

Group 8: Melissa . Mohini. Lofton, Brian Haggart...

An Introduction of

An Introduction of

  • alida-meadow
  • 48 Slides

. Support Vector Machine. Courtesy of . Jinwei. ...

It doesn't matter what you do, but it does matter who does

It doesn't matter what you do, but it does matter who does

  • pasty-toler
  • 14 Slides

Martin Shepperd, Brunel U. Tracy Hall, Brunel U. ...

One Simple Thing To Immediately Make Extreme Classification

One Simple Thing To Immediately Make Extreme Classification

  • pamella-moone
  • 51 Slides

Find Out What Rachel McAdams and Harrison Ford ha...

CS 478 - Learning Rules

CS 478 - Learning Rules

  • sherrill-nordquist
  • 14 Slides

1. Learning Sets of Rules. CS 478 - Learning Rule...

Machine Learning 10-601

Machine Learning 10-601

  • ellena-manuel
  • 52 Slides

Tom M. Mitchell. Machine Learning Department. Car...

ADL aspects of

ADL aspects of

  • pamella-moone
  • 62 Slides

AEmilia. Dipartimento. . di. . Dipartimento di ...

La escuela

La escuela

  • giovanna-bartolotta
  • 9 Slides

de los . padres. La participation des parents à...

Predicting zero-day software vulnerabilities through data-m

Predicting zero-day software vulnerabilities through data-m

  • stefany-barnette
  • 32 Slides

--Third Presentation. Su Zhang. 1. Outline. Quick...

CL Research ACL 2014

CL Research ACL 2014

  • conchita-marotz
  • 16 Slides

1. Pattern Dictionary of English Prepositions. (P...

SUPER: Towards Real-time Event Recognition in Internet Vide

SUPER: Towards Real-time Event Recognition in Internet Vide

  • alexa-scheidler
  • 16 Slides

Yu-Gang . Jiang. School of Computer Science. Fuda...

E fficient

E fficient

  • giovanna-bartolotta
  • 45 Slides

. SAT . S. olving. u. nder. A. ssumptions. Ale...

Joint Object-Material Category

Joint Object-Material Category

  • tatiana-dople
  • 28 Slides

Segmentation from Audio-Visual . Cues. Anurag Arn...

CS240A Final

CS240A Final

  • cheryl-pisano
  • 9 Slides

Project 2. Final for  CS240A: Project . II:. Dat...

Learning to Extract

Learning to Extract

  • stefany-barnette
  • 34 Slides

CSCI-GA.2590. . Ralph . Grishman. NYU. Flavors o...

Performance Anomalies Within The Cloud

Performance Anomalies Within The Cloud

  • luanne-stotts
  • 28 Slides

1. This slide includes content from slides by . V...

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