'Expected error' presentation slideshows

Hierarchical Subquery Evaluation for Active Learning on a Graph

Hierarchical Subquery Evaluation for Active Learning on a Graph. CVPR 2014. Oisin Mac Aodha , Neill Campbell, Jan Kautz , Gabriel Brostow. University College London. Large Image Collections. Cat. Dog. Horse. https:// www.flickr.com/photos/cmichel67. Large Image Collections. Cat.

879 views • 80 slides

The dark-target aerosol remote sensing from MODIS, circa 2011

The dark-target aerosol remote sensing from MODIS, circa 2011. Robert Levy (SSAI and NASA/GSFC) Shana Mattoo (SSAI and NASA/GSFC) Lorraine Remer (GSFC ) Bill Ridgway (SSAI and NASA/GSFC) Junqiang Sun (Sigma and NASA/GSFC) Steve Platnick (GSFC ) Richard Kleidman (SSAI/GSFC). MODIS.

642 views • 41 slides

Vapnik-Chervonenkis Dimension

Vapnik-Chervonenkis Dimension. Part I: Definition and Lower bound. PAC Learning model. There exists a distribution D over domain X Examples: <x, c(x)> use c for target function (rather than c t ) Goal: With high probability (1- d ) find h in H such that error(h,c ) < e

527 views • 21 slides

Vapnik-Chervonenkis Dimension

Vapnik-Chervonenkis Dimension. Part I: Definition and Lower bound. PAC Learning model. There exists a distribution D over domain X Examples: <x, c(x)> use c for target function (rather than c t ) Goal: With high probability (1- d ) find h in H such that error(h,c ) < e

216 views • 21 slides

Vapnik-Chervonenkis Dimension

Vapnik-Chervonenkis Dimension. Part II: Lower and Upper bounds. PAC Learning model. There exists a distribution D over domain X Examples: <x, c(x)> Goal: With high probability (1- d ) find h in H such that error(h,c ) < e. Definitions: Projection. Given a concept c over X

170 views • 16 slides

FY09 GIMPAP Project Proposal Title Page Revised: October 31, 2008

310 views • 16 slides

UNECE Conference Work Session on Statistical Data Editing

291 views • 10 slides

UNECE Conference Work Session on Statistical Data Editing

108 views • 10 slides

Predicting GPM Signals with the GPM Satellite Simulator

Predicting GPM Signals with the GPM Satellite Simulator Toshi Matsui , Code 612, NASA GSFC and ESSIC-UMD.

211 views • 6 slides