# Questions tagged [learning-theory]

Questions about the design and analysis of machine learning algorithms.

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### Method for combining derivative free optimization results of different data inputs

I am working on an algorithm that has multiple fixed parameters. The algorithm analyzes time series data and spits out a number. The fixed parameters need to be such that this number is as small as ...
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### Weighting function for Non Uniform Learning

Consider a hypothesis class $H = \cup_{n=1}^{\infty} H_n$, where for every $n\in N$, $H_n$ is finite. Find a weighting function $w : H ->[0, 1]$ such that $\sum_{h \in H} w(h) ≤ 1$ and so that for ...
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### Perceptron - Generalization Bounds & Compression Bounds

A distribution $P$ over $\mathbb{R}^{d} \times\{-1,+1\}$ being $(\gamma, R)$ -separable. We now let $\mathcal{P}_{\gamma}$ denote the set of all $(\gamma, 1)$ separable distributions. For a ...
110 views

### Sample compression scheme and bounding the VC dimension

There is a compression function takes any sample $S$, for which there exists a function $h ∈ H$ with $L_S(h)$, and compresses it to a subset of $k$ sample points. Similarly, there is a decompression ...
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### Empirical Risk and True Risk - Generalization Error Proof

I showed that, over an uncountable domain,learner A and a distribution P, such that for every sample size m and all samples S from $P^m$ $$: L_S(A(S)) − L_P (A(S))| = 1$$ Now I wanna prove for ...