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15
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Proof of the information bottleneck equations

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#statistical-inference #machine-learning #information-theory #mutual-information
88
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Shattering of a set of binary classifiers

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#combinatorics #computational-complexity #machine-learning
30
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Finding the dual of a problem $\min_{w,b} \sum_{j=1}^{n}{\max(0,w_j)}$

Published on
#optimization #convex-optimization #machine-learning #duality-theorems
75
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Derivation in paper Deep Neural Networks as Gaussian processes in ICLR 2018

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#probability-theory #proof-explanation #machine-learning #neural-networks #gaussian
119
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Upper bound for Telescoping sum in gradient descent

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#inequality #machine-learning #gradient-descent #telescopic-series
325
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Vector form of a polynomial in multiple variables.

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#polynomials #vectors #machine-learning
275
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Definition of "Bias" in Machine learning models

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#machine-learning
53
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Bagging Linear Model?

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#statistical-inference #machine-learning #variance #linear-regression #bootstrap-sampling
221
Views

What was so "Groundbreaking" about Bellman's Equations?

Published on
#optimization #game-theory #machine-learning #dynamic-programming
111
Views

Smooth traversal of ()

Published on
#smooth-manifolds #machine-learning #orthogonal-matrices
940
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Relationship Between Bayesian Optimization and Gaussian Process

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#statistics #optimization #normal-distribution #machine-learning
21
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"Manipulating" Normal Distributions

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#probability #matrices #statistics #normal-distribution #machine-learning
49
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Complexity of Lebesgue measurable spaces

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#measure-theory #statistics #normed-spaces #lp-spaces #machine-learning
17
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A question on the projection step of Generic Adaptive Method: $x_{t+1} = \Pi_{\mathcal{F},\sqrt{V_t}} (\hat{x}_{t+1}).$

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#optimization #convex-optimization #machine-learning #nonlinear-optimization #numerical-optimization
47
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Parameter Estimation in a Gaussian Environment

Published on
#machine-learning #neural-networks

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