Results 11 to 20 of about 38,654 (260)
Iterative Forward-Backward Pursuit Algorithm for Compressed Sensing [PDF]
It has been shown that iterative reweighted strategies will often improve the performance of many sparse reconstruction algorithms. Iterative Framework for Sparse Reconstruction Algorithms (IFSRA) is a recently proposed method which iteratively enhances ...
Feng Wang +3 more
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A Generalization of Forward-backward Algorithm [PDF]
Structured prediction has become very important in recent years. A simple but notable class of structured prediction is one for sequences, so-called sequential labeling. For sequential labeling, it is often required to take a summation over all the possible output sequences, when estimating the parameters of a probabilistic model for instance.
Azuma, Ai, Matsumoto, Yuji
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Accelerated and Inexact Forward-Backward Algorithms [PDF]
We propose a convergence analysis of accelerated forward-backward splitting methods for composite function minimization, when the proximity operator is not available in closed form, and can only be computed up to a certain precision. We prove that the $1/k^2$ convergence rate for the function values can be achieved if the admissible errors are of a ...
VILLA, SILVIA +3 more
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A Forward-Backward Abstraction Refinement Algorithm [PDF]
Abstraction refinement-based model checking has become a standard approach for efficiently verifying safety properties of hardware/software systems. Abstraction refinement algorithms can be guided by counterexamples generated from abstract transition systems or by fixpoints computed in abstract domains.
RANZATO, FRANCESCO +2 more
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An Inertial Forward-Backward Algorithm for Monotone Inclusions [PDF]
The final publication is available at http://link.springer ...
Dirk A. Lorenz, Thomas Pock
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Bayesian Recurrent Units and the Forward-Backward Algorithm
Using Bayes's theorem, we derive a unit-wise recurrence as well as a backward recursion similar to the forward-backward algorithm. The resulting Bayesian recurrent units can be integrated as recurrent neural networks within deep learning frameworks, while retaining a probabilistic interpretation from the direct correspondence with hidden Markov models.
Alexandre Bittar, Philip N. Garner
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Modified Inertial Forward–Backward Algorithm in Banach Spaces and Its Application
In this paper, we present a new modified inertial forward–backward algorithm for finding a common solution of the quasi-variational inclusion problem and the variational inequality problem in a q-uniformly smooth Banach space.
Yanlai Song, Mihai Postolache
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An inertially constructed forward–backward splitting algorithm in Hilbert spaces
In this paper, we develop an iterative algorithm whose architecture comprises a modified version of the forward–backward splitting algorithm and the hybrid shrinking projection algorithm.
Yasir Arfat +4 more
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Silicon nanowire field-effect transistors are promising devices used to detect minute amounts of different biological species. We introduce the theoretical and computational aspects of forward and backward modeling of biosensitive sensors.
Amirreza Khodadadian +3 more
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The forward–backward envelope for sampling with the overdamped Langevin algorithm
AbstractIn this paper, we analyse a proximal method based on the idea of forward–backward splitting for sampling from distributions with densities that are not necessarily smooth. In particular, we study the non-asymptotic properties of the Euler–Maruyama discretization of the Langevin equation, where the forward–backward envelope is used to deal with ...
Armin Eftekhari +2 more
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