All Questions
Tagged with machine-learning oc.optimization-and-control
9
questions
1
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0
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69
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Curve fitting with "rough" loss functions
Many real-valued classification and regression problems can be framed as minimization in the following way.
Setup:
Let $\Theta \in \mathbb{R}^p$ be the parameter space that we are searching over.
For ...
- 190
1
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106
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Can I minimize a mysterious function by running a gradient decent on her neural net approximations? [closed]
A cross post from on AI StackExchange.
So I have this function let call her $F:[0,1]^n \rightarrow \mathbb{R}$ and say $10 \le n \le 100$. I want to find some $x_0 \in [0,1]^n$ such that $F(x_0)$ is ...
- 1,018
1
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98
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Limit cycles or stable solutions for k-dimensional piece-wise linear ODEs
As a branch of reinforcement learning, restless multi-armed bandits have been shown PSPACE-HARD but Whittle has offered an implementable solution called the Whittle Index Policy. Weber and Weiss ...
4
votes
1
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927
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The ODE modeling for gradient descent with decreasing step sizes
The gradient descent (GD) with constant stepsize $\alpha^{k}=\alpha$ takes the form
$$x^{k+1} = x^{k} -\alpha\nabla f(x^{k}).$$
Then, by constructing a continuous-time version of GD iterates ...
- 63
1
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79
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Relation between minimizer of regularized risk & risk in statistical learning theory
In supervised machine learning, we typically take a Risk Minimization (RM) point of view when formulating a problem. So, what we typically solve for is the following:
$$ R^L(h) = \underset{h\in\...
- 11
53
votes
5
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Why do bees create hexagonal cells ? (Mathematical reasons)
Question 0 Are there any mathematical phenomena which are related to the form of honeycomb cells?
Question 1 Maybe hexagonal lattices satisfy certain optimality condition(s) which are related to it? ...
- 24.4k
7
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1
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Does the plane clustered to minimize sum distances^2 to clusters centers ( inertia / "K-means") produce hexagonal clusters / hexagonal lattice?
"K-means" is the most simple and famous clustering algorithm, which has numerous applications.
For a given as an input number of clusters it segments set of points in R^n to that given number of ...
- 24.4k
1
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0
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187
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Solution to a Strongly Convex Non-smooth Minimization Problem involving an L1 Norm
Let $X \in \mathbb{R}^{n \times d}, w \in \mathbb{R}^d, y \in \{\pm 1\}^{n}, \alpha \in [0,1], \lambda \in \mathbb{R}$. I have an expression that looks as follows
$\frac{1}{2}\|Xw -y \|_{2}^2 + \...
- 11
1
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2
answers
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Is it possible to “solve” iterative (convex/non-convex) optimization problems via learning (one-shot)?
I posted a following question in MSE, but I think it should be posted here in MO. Since I don't know how to transfer the post from MSE to MO, I have pasted the question below. Thank you in advance and ...
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