Competitive learning and soft competition for vector quantizerdesign

The authors provide a convergence analysis for the Kohonen learning algorithm (KLA) with respect to vector quantizer (VQ) optimality criteria and introduce a stochastic relaxation technique which produces the global minimum but is computationally expensive. By incorporating the principles of the stochastic approach into the KLA, a deterministic VQ design algorithm, the soft competition scheme (SCS), is introduced. Experimental results are presented where the SCS consistently provided better codebooks than the generalized Lloyd algorithm (GLA), even when the same computation time was used for both algorithms. The SCS may therefore prove to be a valuable alternative to the GLA for VQ design     

Kernel machines for current status data

Machine Learning - In survival analysis, estimating the failure time distribution is an important and difficult task, since usually the data is subject to censoring. Specifically, in this paper we...     

Potassium sorbate solutions as copper chemical mechanical planarization (CMP) based slurries

Copper depassivation and repassivation characteristics in potassium sorbate solutions, subsequent to mechanical abrading are reported. The identification of copper repassivation kinetics obtained subsequent to mechanical damage of copper protective films formed in sorbate based solutions is discussed. The repassivation rate of copper in sorbate based solutions was measured by means of a slurryjet system capable of measuring single particle impingments on microelectrodes. Copper repassivation rates measured by this slurryjet system in sulfate solutions containing 10 g L⁻¹ potassium sorbate were found to be in the range of 0.5-1.5 ms. An increase in the potassium sorbate concentration leads to a decrease in copper repassivation time at potentials ranging from 200 to 600 mV_Ag/AgCl. The impingement angle between the copper surface and a single abrasive particle has no impact on copper repassivation time nor peak current (I_max) values. XPS studies revealed that copper passivation in potassium based solution was due to the formation of a thin film which is constituted of: Cu₂O, Cu(OH)₂ and Cu(II)-sorbate, while copper(II)-sorbate is mainly present at the top levels of the passive film. It is therefore recommended that the use of potassium sorbate as a passivating component in conjunction with the addition of strong oxidizing agents in chemical mechanical planarization (CMP) slurry design should be considered.     

Fusing distributional and experiential information for measuring semantic relatedness

Models of semantic relatedness have usually focused on language-based distributional information without taking into account “experiential data” concerning the embodied sensorial source of the represented concepts. In this paper, we present an integrative cognitive model of semantic relatedness. The model – semantic family resemblance – uses a variation of the co-product as a mathematical structure that guides the fusion of distributional and experiential information. Our algorithm provides superior results in a set expansion task and a significant correlation with two benchmarks of human rated word-pair similarity datasets.     

Steward: Scaling Byzantine Fault-Tolerant Replication to Wide Area Networks

This paper presents the first hierarchical Byzantine fault-tolerant replication architecture suitable to systems that span multiple wide-area sites. The architecture confines the effects of any malicious replica to its local site, reduces message complexity of wide-area communication, and allows read-only queries to be performed locally within a site for the price of additional standard hardware. We present proofs that our algorithm provides safety and liveness properties. A prototype implementation is evaluated over several network topologies and is compared with a flat Byzantine fault-tolerant approach. The experimental results show considerable improvement over flat Byzantine replication algorithms, bringing the performance of Byzantine replication closer to existing benign fault-tolerant replication techniques over wide area networks.     

Simple fiber-optic confocal microscopy with nanoscale depth resolution beyond the diffraction barrier

A novel fiber-optic confocal approach for ultrahigh depth-resolution (相似文献   

User assisted separation of reflections from a single image using a sparsity prior

When we take a picture through transparent glass the image we obtain is often a linear superposition of two images: the image of the scene beyond the glass plus the image of the scene reflected by the glass. Decomposing the single input image into two images is a massively ill-posed problem: in the absence of additional knowledge about the scene being viewed there are an infinite number of valid decompositions. In this paper we focus on an easier problem: user assisted separation in which the user interactively labels a small number of gradients as belonging to one of the layers. Even given labels on part of the gradients, the problem is still ill-posed and additional prior knowledge is needed. Following recent results on the statistics of natural images we use a sparsity prior over derivative filters. This sparsity prior is optimized using the terative reweighted least squares (IRLS) approach. Our results show that using a prior derived from the statistics of natural images gives a far superior performance compared to a Gaussian prior and it enables good separations from a modest number of labeled gradients.     

On the string averaging method for sparse common fixed-point problems

We study the common fixed-point problem for the class of directed operators. This class is important because many commonly used nonlinear operators in convex optimization belong to it. We propose a definition of sparseness of a family of operators and investigate a string-averaging algorithmic scheme that favorably handles the common fixed-point problem when the family of operators is sparse. The convex feasibility problem is treated as a special case and a new subgradient projections algorithmic scheme is obtained.