Technion – Israel Institute of Technology
About: Technion – Israel Institute of Technology is a(n) education organization based out in Haifa, Israel. It is known for research contribution in the topic(s): Population & Upper and lower bounds. The organization has 31714 authors who have published 79377 publication(s) receiving 2603976 citation(s). The organization is also known as: Technion Israel Institute of Technology & Ṭekhniyon, Makhon ṭekhnologi le-Yiśraʼel.
Topics: Population, Upper and lower bounds, Nonlinear system, Decoding methods, Large Hadron Collider
Papers published on a yearly basis
TL;DR: A new fast iterative shrinkage-thresholding algorithm (FISTA) which preserves the computational simplicity of ISTA but with a global rate of convergence which is proven to be significantly better, both theoretically and practically.
Abstract: We consider the class of iterative shrinkage-thresholding algorithms (ISTA) for solving linear inverse problems arising in signal/image processing. This class of methods, which can be viewed as an extension of the classical gradient algorithm, is attractive due to its simplicity and thus is adequate for solving large-scale problems even with dense matrix data. However, such methods are also known to converge quite slowly. In this paper we present a new fast iterative shrinkage-thresholding algorithm (FISTA) which preserves the computational simplicity of ISTA but with a global rate of convergence which is proven to be significantly better, both theoretically and practically. Initial promising numerical results for wavelet-based image deblurring demonstrate the capabilities of FISTA which is shown to be faster than ISTA by several orders of magnitude.
Georges Aad1, T. Abajyan2, Brad Abbott3, Jalal Abdallah4 +2964 more•Institutions (200)
17 Sep 2012-Physics Letters B
TL;DR: In this article, a search for the Standard Model Higgs boson in proton-proton collisions with the ATLAS detector at the LHC is presented, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9.
Abstract: A search for the Standard Model Higgs boson in proton–proton collisions with the ATLAS detector at the LHC is presented. The datasets used correspond to integrated luminosities of approximately 4.8 fb−1 collected at View the MathML source in 2011 and 5.8 fb−1 at View the MathML source in 2012. Individual searches in the channels H→ZZ(⁎)→4l, H→γγ and H→WW(⁎)→eνμν in the 8 TeV data are combined with previously published results of searches for H→ZZ(⁎), WW(⁎), View the MathML source and τ+τ− in the 7 TeV data and results from improved analyses of the H→ZZ(⁎)→4l and H→γγ channels in the 7 TeV data. Clear evidence for the production of a neutral boson with a measured mass of View the MathML source is presented. This observation, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9, is compatible with the production and decay of the Standard Model Higgs boson.
TL;DR: A novel algorithm for adapting dictionaries in order to achieve sparse signal representations, the K-SVD algorithm, an iterative method that alternates between sparse coding of the examples based on the current dictionary and a process of updating the dictionary atoms to better fit the data.
Abstract: In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and include compression, regularization in inverse problems, feature extraction, and more. Recent activity in this field has concentrated mainly on the study of pursuit algorithms that decompose signals with respect to a given dictionary. Designing dictionaries to better fit the above model can be done by either selecting one from a prespecified set of linear transforms or adapting the dictionary to a set of training signals. Both of these techniques have been considered, but this topic is largely still open. In this paper we propose a novel algorithm for adapting dictionaries in order to achieve sparse signal representations. Given a set of training signals, we seek the dictionary that leads to the best representation for each member in this set, under strict sparsity constraints. We present a new method-the K-SVD algorithm-generalizing the K-means clustering process. K-SVD is an iterative method that alternates between sparse coding of the examples based on the current dictionary and a process of updating the dictionary atoms to better fit the data. The update of the dictionary columns is combined with an update of the sparse representations, thereby accelerating convergence. The K-SVD algorithm is flexible and can work with any pursuit method (e.g., basis pursuit, FOCUSS, or matching pursuit). We analyze this algorithm and demonstrate its results both on synthetic tests and in applications on real image data
TL;DR: This review discusses recent information on functions and mechanisms of the ubiquitin system and focuses on what the authors know, and would like to know, about the mode of action of ubi...
Abstract: The selective degradation of many short-lived proteins in eukaryotic cells is carried out by the ubiquitin system. In this pathway, proteins are targeted for degradation by covalent ligation to ubiquitin, a highly conserved small protein. Ubiquitin-mediated degradation of regulatory proteins plays important roles in the control of numerous processes, including cell-cycle progression, signal transduction, transcriptional regulation, receptor down-regulation, and endocytosis. The ubiquitin system has been implicated in the immune response, development, and programmed cell death. Abnormalities in ubiquitin-mediated processes have been shown to cause pathological conditions, including malignant transformation. In this review we discuss recent information on functions and mechanisms of the ubiquitin system. Since the selectivity of protein degradation is determined mainly at the stage of ligation to ubiquitin, special attention is focused on what we know, and would like to know, about the mode of action of ubiquitin-protein ligation systems and about signals in proteins recognized by these systems.
TL;DR: The compression ratio achieved by the proposed universal code uniformly approaches the lower bounds on the compression ratios attainable by block-to-variable codes and variable- to-block codes designed to match a completely specified source.
Abstract: A universal algorithm for sequential data compression is presented. Its performance is investigated with respect to a nonprobabilistic model of constrained sources. The compression ratio achieved by the proposed universal code uniformly approaches the lower bounds on the compression ratios attainable by block-to-variable codes and variable-to-block codes designed to match a completely specified source.
Showing all 31714 results
|Nicholas G. Martin||192||1770||161952|
|Tobin J. Marks||159||1621||111604|
|Grant W. Montgomery||157||926||108118|
|David J. Mooney||156||695||94172|
|Jerrold M. Olefsky||143||595||77356|
|Joseph J.Y. Sung||142||1240||92035|
|Jerry W. Shay||133||639||74774|
|Richard N. Bergman||130||477||91718|
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