the determinants of product variety for a traditional firm that follows the first approach; compare it to a customizing firm; derive the optimal decisions of a dual-channel firm that operates both a traditional and a customizing channel; and study the results of competition between the two types of firms

de/ls_schmidt/index.html

We develop a face recognition algorithm which is insensitive to gross variation in lighting direction and facial expression. Taking a pattern classification approach, we consider each pixel in an image as a coordinate in a high-dimensional space. We take advantage of the observation that the images of a particular face, under varying illumination but fixed pose, lie in a 3-D linear subspace of the high dimensional image space -- if the face is a Lambertian surface without shadowing. However, since faces are not truly Lambertian surfaces and do indeed produce self-shadowing, images will deviate from this linear subspace. Rather than explicitly modeling this deviation, we linearly project the image into a subspace in a manner which discounts those regions of the face with large deviation. Our projection method is based on Fisher's Linear Discriminant and produces well separated classes in a low-dimensional subspace even under severe variation in lighting and facial expressions. The Eigenface

Abstract not found

Today’s business enterprises must deal with global competition, reduce the cost of doing business, and rapidly develop new services and products. To address these requirements enterprises must constantly reconsider and optimize the way they do business and change their information systems

because the incentives may crowd out voluntary co-operation. It strongly limits the effects of competition in markets with incomplete contracts and gives rise to noncompetitive wage differences. Finally, reciprocity it is also a strong force contributing to the existence of incomplete contracts.

Abstract – The Internet is rapidly growing in number of users, traffic levels, and topological complexity. At the same time it is increasingly driven by economic competition. These developments render the characterization of network usage and workloads more difficult, and yet more critical. Few

rates higher than those of C4.5 and C4.5rules. We then propose a number of modifications resulting in an algorithm RIPPERk that is very competitive with C4.5rules with respect to error rates, but much more efficient on large samples. RIPPERk obtains error rates lower than or equivalent to C4.5rules

additive components are regression trees, and tools for interpreting such \TreeBoost" models are presented. Gradient boosting of regression trees produces competitive, highly robust, interpretable procedures for both regression and classication, especially appropriate for mining less than clean

This paper empirically investigates the effects of liberalized trade on plant productivity in the case of Chile. Chile presents an interesting setting to study this relationship since it underwent a massive trade liberalization that significantly exposed its plants to competition from abroad during