Question

Adding nodes to graphs while preserving harmonic solution

score 53 · Answer 1 · 2026-03-25 15:45:32

53

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Adding nodes to graphs while preserving harmonic solution

Published on 25 Mar 2026 - 15:45

score 66 · Answer 2 · 2019-03-08 06:24:15

66

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Are the initial values of the slope, intercept and the learning rate in gradient descent experimental?

Published on 08 Mar 2019 - 6:24

score 809 · Answer 3 · 2019-03-10 18:23:36

809

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Clarification about the $\epsilon$-net argument

Published on 10 Mar 2019 - 18:23

score 616 · Answer 4 · 2019-03-11 04:35:42

616

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Writing action-value function in terms of state-value function for a Markov decision process

Published on 11 Mar 2019 - 4:35

score 31 · Answer 5 · 2019-03-11 05:06:14

31

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Relationship between feature maps of othogonal kernel functions

Published on 11 Mar 2019 - 5:06

score 40 · Answer 6 · 2019-03-12 08:50:38

40

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Proofing of euclidean distance for vectors

Published on 12 Mar 2019 - 8:50

score 6.1k · Answer 7 · 2026-03-25 09:43:48

6.1k

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What are the best books to study Neural Networks from a purely mathematical perspective?

Published on 25 Mar 2026 - 9:43

score 39 · Answer 8 · 2019-03-13 16:52:14

39

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A similarity metric for sets

Published on 13 Mar 2019 - 16:52

score 416 · Answer 9 · 2026-03-25 05:07:02

416

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Example of "The eigenvalues of data covariance matrix, $\Phi^T\Phi$ measure the curvature of the likelihood function."

Published on 25 Mar 2026 - 5:07

score 144 · Answer 10 · 2026-03-25 09:53:51

144

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Finding the M.L.E estimates of weight maximizing the Likelihood Function of a Linear Regression

Published on 25 Mar 2026 - 9:53

score 155 · Answer 11 · 2019-03-14 22:36:07

155

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How to reconcile difference in notation used in probability and statistics by different authors

Published on 14 Mar 2019 - 22:36

score 248 · Answer 12 · 2019-03-14 23:03:55

248

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Rademacher complexity definition

Published on 14 Mar 2019 - 23:03

score 257 · Answer 13 · 2026-03-25 07:57:19

257

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Derivation Contrastive Divergence

Published on 25 Mar 2026 - 7:57

score 81 · Answer 14 · 2019-03-17 12:33:18

81

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The Bayes predictor of the square loss is $\Bbb E_P[Y\mid X=x]$?

Published on 17 Mar 2019 - 12:33

score 47 · Answer 15 · 2019-03-17 13:41:53

47

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Decomposing estimation error into bias and variance

Published on 17 Mar 2019 - 13:41

List Question

Adding nodes to graphs while preserving harmonic solution

Are the initial values of the slope, intercept and the learning rate in gradient descent experimental?

Clarification about the $\epsilon$-net argument

Writing action-value function in terms of state-value function for a Markov decision process

Relationship between feature maps of othogonal kernel functions

Proofing of euclidean distance for vectors

What are the best books to study Neural Networks from a purely mathematical perspective?

A similarity metric for sets

Example of "The eigenvalues of data covariance matrix, $\Phi^T\Phi$ measure the curvature of the likelihood function."

Finding the M.L.E estimates of weight maximizing the Likelihood Function of a Linear Regression

How to reconcile difference in notation used in probability and statistics by different authors

Rademacher complexity definition

Derivation Contrastive Divergence

The Bayes predictor of the square loss is $\Bbb E_P[Y\mid X=x]$?

Decomposing estimation error into bias and variance

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