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15
Math.TechQA.Club
2026-04-01 04:20:24
168
Views
Lagrangian multiplier with an equality constraint and an inequality constraint
Published on
01 Apr 2026 - 4:20
#optimization
#machine-learning
#lagrange-multiplier
#maximum-likelihood
162
Views
Growth function $\tau_{\mathcal{H}}(m)$ lower bound
Published on
21 Oct 2021 - 10:08
#probability-theory
#statistics
#machine-learning
948
Views
Difference between EPE and MSE
Published on
11 Apr 2026 - 1:01
#statistics
#machine-learning
124
Views
How to compute the dual of an optimization problem defined on a function space?
Published on
11 Apr 2026 - 5:00
#statistics
#optimization
#machine-learning
439
Views
Gram Matrix and Covariance Matrix
Published on
22 Oct 2021 - 23:54
#linear-algebra
#machine-learning
60
Views
How do I take the derivative of integral with respect to a function?
Published on
10 Apr 2026 - 1:58
#calculus
#integration
#multivariable-calculus
#indefinite-integrals
#machine-learning
71
Views
ANOVA Kernel: Show that $K_a(x,t)=\langle\phi_a(x),\phi_a(t)\rangle,\forall x,t\in\mathbb{R}^n$
Published on
24 Oct 2021 - 14:20
#induction
#machine-learning
116
Views
An optimal solution for a sparse linear regression model
Published on
11 Apr 2026 - 15:33
#optimization
#convex-analysis
#convex-optimization
#machine-learning
#non-convex-optimization
526
Views
Is $K(x,t)=\exp(x_1t_1)$ a valid kernel?
Published on
24 Oct 2021 - 21:22
#inner-products
#machine-learning
#positive-definite
31
Views
confused about beta weights in logistic regression
Published on
27 Mar 2026 - 2:38
#graphing-functions
#machine-learning
#regression
#linear-regression
#logistic-regression
47
Views
Is there an universal continuous probability distribution approximator?
Published on
11 Apr 2026 - 0:30
#probability
#probability-theory
#approximation
#machine-learning
#density-function
24
Views
What changes is the Neural Network back-propagation algorithm doing on the weights?
Published on
11 Apr 2026 - 6:58
#graph-theory
#algorithms
#machine-learning
#discrete-optimization
#neural-networks
245
Views
Proof of $\frac{1}{n}\mathrm{E} \left[ \| \mathbf{X}\mathbf{\hat{w}} - \mathbf{X}\mathbf{w}^{*} \|^{2}_{2} \right] = \sigma^{2}\frac{d}{n}$
Published on
31 Mar 2026 - 7:52
#statistics
#proof-explanation
#machine-learning
#linear-regression
#pseudoinverse
951
Views
Feature vector concatenation
Published on
29 Oct 2021 - 13:19
#linear-algebra
#vectors
#machine-learning
443
Views
Determine the orthogonal projection $\pi_{U}(e_{2})$ of $e_{2}$ onto $U$
Published on
07 Apr 2026 - 12:48
#linear-algebra
#geometry
#vector-spaces
#machine-learning
#projective-geometry
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