approach with Eigenface and Fisherface methods on three different face data sets. Experimental results suggest that the proposed Laplacianface approach provides a better representation and achieves lower error rates in face recognition. Index Terms—Face recognition, principal component analysis, linear

texture or piecewise smooth). The use of the BPDN with the two augmented dictionaries leads to the desired separation, along with noise removal as a by-product. As the need to choose proper dictionaries is generally hard, a TV regularization is employed to better direct the separation process and reduce

We construct supersymmetric theories in which the correct scale for electroweak symmetry breaking is obtained without significant fine-tuning. We calculate the fine-tuning parameter for these theories to be at the 20 % level, which is significantly better than in conventional supersymmetry breaking

discriminant analysis, logistic regression, and neural networks. We demonstrate that the classifiers perform 1015 % better than relevance feedback via Rocchio expansion for the TREC-2 and TREC-3 routing tasks. Error minimization is difficult in high-dimensional feature spaces because the convergence process

together with a local application of mirror symmetry. This construction is not based on any duality conjecture and thus reduces non-trivial quantum field theory results to much better understood T-dualities of type II strings. Moreover it can be used in principle to construct in a systematic way the vacuum

. Based on our results, we believe that fine-tuned heuristics may provide truly scalable solutions to the influence maximization problem with satisfying influence spread and blazingly fast running time. Therefore, contrary to what implied by the conclusion of [5] that traditional heuristics

is excessive. GUT threshold correction to the universal Higgs mass parameter can significantly reduce the fine-tuning required for such large values of tan β. We also point out that the top quark mass can play a crucial role in explaining the hierarchy between the SUSY breaking scale and the electro-weak scale

not exceed processing capacity, and which are processed serially. Conceptual chunking entails "collapsing" representations to reduce their dimensionality and consequently their processing load, but at the cost of making some relational information inaccessible. Parallel distributed processing

We construct supersymmetric theories in which the correct scale for electroweak symmetry breaking is obtained without significant fine-tuning. We calculate the fine-tuning parameter for these theories to be at the 20 % level, which is significantly better than in conventional supersymmetry breaking

to work with crosscutting concerns by providing better support for exploring code. Our tool helps the developer to remain ori-ented while exploring and navigating across a code base. The cognitive burden placed on a developer is reduced by avoiding disorienting view switches and by providing an ex