W Y W X W Y WX W Y WX W Y WX O O X X O O O - - PowerPoint PPT Presentation

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W Y W X W Y WX W Y WX W Y WX O O X X O O O - - PowerPoint PPT Presentation

W Y W X W Y WX W Y WX W Y WX O O X X O O O X O O X O O M M O O E E E O O E O E O E E O O O E vs. E O O O O E X O E E F O O O O O O E


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W

X W Y   

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W WX Y 

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W WX Y 

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W WX Y 

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O O O O O X X X O X O

↑ ↓

O

↓ ↑

O

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M

M

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O X O O O O O O O O O O O O O O O O O O OO O E E E E E E E E E E E E E E E E E E E F vs.

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Computational Costs:

During Learning

1,000 2,000 3,000 4,000 5,000 6,000 7,000 Computing Time (s)

SVM Learning (W) Fastest Feedforward Learning (W) Illuminated Learning (M)

Out of Memory!

5 10 15 20 Matrix Size Million

Out of Memory!

… 120 !

SVM F

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2 4 6 8 10 Computational Cost per Test (s)

Computational Costs:

During Recognition

Best Alternate AI (KNN)

Without Optimization

Illuminated AI (M) Matrix Size 50 100 Millions 20 120 Feedforward AI (W)

SVM F Out of Memory!

Even Faster with Converted Networks

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– –

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  • 0.25 -0.2
  • 0.15 -0.1
  • 0.05

0.05 0.1 0.15 2 4 6 8 10 12 2 4 6 8 10 12 14

  • 0.5

0.5 1 1.5 0.6

  • 0.2
  • 0.1

0.1 0.2 0.3 0.4 0.5 5 10 15 20 25

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I1 W11 W12 * I2 + W13 * I3 + … … W11 * I1 O1 =

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  • 1

2 3 4 5 6 7 8 9

Ideal "Expected" Patterns

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