By José L. Balcázar, Philip M. Long, Frank Stephan

ISBN-10: 3540466495

ISBN-13: 9783540466499

This publication constitutes the refereed court cases of the seventeenth overseas convention on Algorithmic studying idea, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the ninth overseas convention on Discovery technology, DS 2006.

The 24 revised complete papers awarded including the abstracts of 5 invited papers have been conscientiously reviewed and chosen from fifty three submissions. The papers are devoted to the theoretical foundations of laptop studying. They handle subject matters corresponding to question versions, online studying, inductive inference, algorithmic forecasting, boosting, help vector machines, kernel equipment, reinforcement studying, and statistical studying models.

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José L. Balcázar, Philip M. Long, Frank Stephan's Algorithmic Learning Theory: 17th International Conference, PDF

This e-book constitutes the refereed lawsuits of the seventeenth overseas convention on Algorithmic studying concept, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the ninth foreign convention on Discovery technology, DS 2006. The 24 revised complete papers awarded including the abstracts of 5 invited papers have been conscientiously reviewed and chosen from fifty three submissions.

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Additional resources for Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006. Proceedings

Sample text

Let ωb = e b and for each α = (α1 , . . , αn ) ∈ [b]n , let χα : [b]n → C be defined as χα (x) = ωbα1 x1 +···+αn xn . Let B denote the set of functions B = {χα : α ∈ [b]n }. It is easy to verify the following properties: – For each α = (α1 , . . , αn ) ∈ [b]n , we have χα = 1. 1 if α = β . 0 if α = β – B constitutes an orthonormal basis for all functions {f : [b]n → C} considered as a vector space over C, so every f : [b]n → C can be expressed uniquely as f (x) = α fˆ(α)χα (x), which we refer to as the Fourier expansion or Fourier transform of f .

The functions we study. The reader might wonder which classes of Boolean valued functions over [b]n are interesting. In this article we study classes of functions that are defined in terms of “b-literals”; these include rectangles and unions of rectangles over [b]n as well as other richer classes. As described below, b-literals are a natural extension of Boolean literals to the domain [b]n . Definition 1. A function : [b] → {−1, 1} is a basic b-literal if for some σ ∈ {−1, 1} and some α ≤ β with α, β ∈ [b] we have (x) = σ if α ≤ x ≤ β, and (x) = −σ otherwise.

Corollary 9. If HNP[MSB] is properly PAC learnable under the uniform distribution, then the unbiased most significant bit of the Diffie-Hellman function is secure. To the best of our knowledge, it is not known whether HNP[MSB] is properly PAC learnable under the uniform distribution. However, from our general lower bound on the number of statistical queries, we can infer the following result: Lemma 3. For every n-bit prime, L(HNP[MSB]n ) = p1−o(1) . Proof. Consider the multiplication table M ∈ (Z∗p )(p−1)×(p−1) .

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Algorithmic Learning Theory: 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006. Proceedings by José L. Balcázar, Philip M. Long, Frank Stephan


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