Results 1 - 10 of 15,906

Optimally sparse representation in general (non-orthogonal) dictionaries via ℓ¹ minimization

by David L. Donoho, Michael Elad - PROC. NATL ACAD. SCI. USA 100 2197–202 , 2002
"... Given a ‘dictionary’ D = {dk} of vectors dk, we seek to represent a signal S as a linear combination S = ∑ k γ(k)dk, with scalar coefficients γ(k). In particular, we aim for the sparsest representation possible. In general, this requires a combinatorial optimization process. Previous work considered ..."
Abstract - Cited by 633 (38 self) - Add to MetaCart
optimization problem: specifically, minimizing the ℓ¹ norm of the coefficients γ. In this paper, we obtain parallel results in a more general setting, where the dictionary D can arise from two or several bases, frames, or even less structured systems. We introduce the Spark, ameasure of linear dependence

Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy

by Hanchuan Peng, Fuhui Long, Chris Ding - IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2005
"... Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we first der ..."
Abstract - Cited by 571 (8 self) - Add to MetaCart
Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we first

Do grammars minimize dependency length

by Daniel Gildea, A David Temperleyb - Cognitive Science , 2010
"... A well-established principle of language is that there is a preference for closely related words to be close together in the sentence. This can be expressed as a preference for dependency length mini-mization (DLM). In this study, we explore quantitatively the degree to which natural languages refle ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
A well-established principle of language is that there is a preference for closely related words to be close together in the sentence. This can be expressed as a preference for dependency length mini-mization (DLM). In this study, we explore quantitatively the degree to which natural languages

A new learning algorithm for blind signal separation

by S. Amari, A. Cichocki, H. H. Yang - , 1996
"... A new on-line learning algorithm which minimizes a statistical de-pendency among outputs is derived for blind separation of mixed signals. The dependency is measured by the average mutual in-formation (MI) of the outputs. The source signals and the mixing matrix are unknown except for the number of ..."
Abstract - Cited by 622 (80 self) - Add to MetaCart
A new on-line learning algorithm which minimizes a statistical de-pendency among outputs is derived for blind separation of mixed signals. The dependency is measured by the average mutual in-formation (MI) of the outputs. The source signals and the mixing matrix are unknown except for the number

Minimal Dependency Length in Realization Ranking

by Michael White, Rajakrishnan Rajkumar
"... Comprehension and corpus studies have found that the tendency to minimize dependency length has a strong influence on constituent ordering choices. In this paper, we investigate dependency length minimization in the context of discriminative realization ranking, focusing on its potential to eliminat ..."
Abstract - Cited by 7 (2 self) - Add to MetaCart
Comprehension and corpus studies have found that the tendency to minimize dependency length has a strong influence on constituent ordering choices. In this paper, we investigate dependency length minimization in the context of discriminative realization ranking, focusing on its potential

Survey on Independent Component Analysis

by Aapo Hyvärinen - NEURAL COMPUTING SURVEYS , 1999
"... A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate data. For computational and conceptual simplicity, such a representation is often sought as a linear transformation of the ..."
Abstract - Cited by 2309 (104 self) - Add to MetaCart
of the original data. Well-known linear transformation methods include, for example, principal component analysis, factor analysis, and projection pursuit. A recently developed linear transformation method is independent component analysis (ICA), in which the desired representation is the one that minimizes

Active Contours without Edges

by Tony F. Chan, Luminita A. Vese , 2001
"... In this paper, we propose a new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford--Shah functional for segmentation and level sets. Our model can detect objects whose boundaries are not necessarily defined by gradient. We minimize an energy ..."
Abstract - Cited by 1206 (38 self) - Add to MetaCart
an energy which can be seen as a particular case of the minimal partition problem. In the level set formulation, the problem becomes a "mean-curvature flow"-like evolving the active contour, which will stop on the desired boundary. However, the stopping term does not depend on the gradient

Nonlinear total variation based noise removal algorithms

by Leonid I. Rudin, Stanley Osher, Emad Fatemi , 1992
"... A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lagrange multipliers. The solution is obtained using the g ..."
Abstract - Cited by 2271 (51 self) - Add to MetaCart
A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lagrange multipliers. The solution is obtained using

The BSD Packet Filter: A New Architecture for User-level Packet Capture

by Steven Mccanne, Van Jacobson , 1992
"... Many versions of Unix provide facilities for user-level packet capture, making possible the use of general purpose workstations for network monitoring. Because network monitors run as user-level processes, packets must be copied across the kernel/user-space protection boundary. This copying can be m ..."
Abstract - Cited by 568 (2 self) - Add to MetaCart
be minimized by deploying a kernel agent called a packet filter, which discards unwanted packets as early as possible. The original Unix packet filter was designed around a stack-based filter evaluator that performs sub-optimally on current RISC CPUs. The BSD Packet Filter (BPF) uses a new, registerbased

Energy Conserving Routing in Wireless Ad-hoc Networks

by Jae-hwan Chang, Leandros Tassiulas , 2000
"... An ad-hoc network of wireless static nodes is considered as it arises in a rapidly deployed, sensor based, monitoring system. Information is generated in certain nodes and needs to reach a set of designated gateway nodes. Each node may adjust its power within a certain range that determines the set ..."
Abstract - Cited by 622 (2 self) - Add to MetaCart
the set of possible one hop away neighbors. Traffic forwarding through multiple hops is employed when the intended destination is not within immediate reach. The nodes have limited initial amounts of energy that is consumed in different rates depending on the power level and the intended receiver. We
Results 1 - 10 of 15,906