Results 11 to 20 of about 87,603 (273)
Greedy Algorithms for Optimal Distribution Approximation
The approximation of a discrete probability distribution $\mathbf{t}$ by an $M$-type distribution $\mathbf{p}$ is considered. The approximation error is measured by the informational divergence $\mathbb{D}(\mathbf{t}\Vert\mathbf{p})$, which is an ...
Böcherer, Georg, Geiger, Bernhard C.
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Simultaneous approximation by greedy algorithms [PDF]
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Leviatan, D., Temlyakov, V. N.
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Sparse Approximation and Recovery by Greedy Algorithms [PDF]
We study sparse approximation by greedy algorithms. Our contribution is two-fold. First, we prove exact recovery with high probability of random $K$-sparse signals within $\lceil K(1+\e)\rceil$ iterations of the Orthogonal Matching Pursuit (OMP). This result shows that in a probabilistic sense the OMP is almost optimal for exact recovery.
Livshitz, Eugene, Temlyakov, Vladimir
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Simultaneous optimized orthogonal matching pursuit with application to ECG compression. [PDF]
A greedy pursuit strategy which finds a common basis for approximating a set of similar signals is proposed. The strategy extends the Optimized Orthogonal Matching Pursuit approach to selecting the subspace containing the approximation of all the signals
Rebollo-Neira L.
europepmc +2 more sources
On the convergence of the order-preserving weak greedy algorithm for subspaces generated by the Szego kernel in the Hardy space [PDF]
In this article we consider representing properties of subspaces generated by the Szego kernel. We examine under which conditions on the sequence of points of the unit disk the order-preserving weak greedy algorithm for appropriate subspaces generated by
Speransky, Konstantin Sergeevich
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Approximation Ratios of RePair, LongestMatch and Greedy on Unary Strings
A grammar-based compressor is an algorithm that receives a word and outputs a context-free grammar that only produces this word. The approximation ratio for a single input word is the size of the grammar produced for this word divided by the size of a ...
Danny Hucke, Carl Philipp Reh
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On the Rate of Convergence of Greedy Algorithms
In this paper, a new criterion for the evaluation of the theoretical efficiency of a greedy algorithm is suggested. Using this criterion, we prove some results on the rate of convergence of greedy algorithms, which provide expansions.
Vladimir Temlyakov
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Approximate Weak Greedy Algorithms [PDF]
We present a generalization of V. Temlyakov's weak greedy algorithm, and give a sufficient condition for norm convergence of the algorithm for an arbitrary dictionary in a Hilbert space. We provide two counter-examples to show that the condition cannot be relaxed for general dictionaries.
Gribonval, Rémi, Nielsen, Morten
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Sharp conditions for the convergence of greedy expansions with prescribed coefficients
Greedy expansions with prescribed coefficients were introduced by V. N. Temlyakov in a general case of Banach spaces. In contrast to Fourier series expansions, in greedy expansions with prescribed coefficients, a sequence of coefficients {cn}n=1∞{\left\{{
Valiullin Artur R., Valiullin Albert R.
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Approximation Properties of the Vector Weak Rescaled Pure Greedy Algorithm
We first study the error performances of the Vector Weak Rescaled Pure Greedy Algorithm for simultaneous approximation with respect to a dictionary D in a Hilbert space.
Xu Xu +3 more
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