Abstract not found

scenarios where the lasso is inconsistent for variable selection. We then propose a new version of the lasso, called the adaptive lasso, where adaptive weights are used for penalizing different coefficients in the!1 penalty. We show that the adaptive lasso enjoys the oracle properties; namely, it performs

Performance modelling is concerned with the capture and analysis of the dynamic behaviour of computer and communication systems. The size and complexity of many modern systems result in large, complex models. A compositional approach decomposes the system into subsystems that are smaller and more

In this paper we compare the performance of descriptors computed for local interest regions, as for example extracted by the Harris-Affine detector [32]. Many different descriptors have been proposed in the literature. However, it is unclear which descriptors are more appropriate and how

A new image compression algorithm is proposed, based on independent Embedded Block Coding with Optimized Truncation of the embedded bit-streams (EBCOT). The algorithm exhibits state-of-the-art compression performance while producing a bit-stream with a rich feature set, including resolution and SNR

of the model and the properties of the performance measure suggested here are discussed in Section II. The evidence on mutual fund performance indicates not only that these 115 mutual funds were on average not able to predict security prices well enough to outperform a buy-the-marketand-hold policy, but also

We prove symmetry, and some related properties, of positive solutions of second order elliptic equations. Our methods employ various forms of the maximum principle, and a device of moving parallel planes to a critical position, and then showing that the solution is symmetric about the limiting

these generalized sequential patterns. Empirical evaluation using synthetic and real-life data indicates that GSP is much faster than the AprioriAll algorithm presented in [3]. GSP scales linearly with the number of data-sequences, and has very good scale-up properties with respect to the average datasequence size

The development ofa 2 l-item self-report inventory for measuring the severity of anxiety in psychiat-ric populations i described. The initial item pool f86 items was drawn from three preexisting scales: the Anxiety Checklist, the Physician's Desk Reference Checklist, and the Situational Anxiety Checklist. A series of analyses was used to reduce the item pool. The resulting Beck Anxiety Inven-tory (BAI) is a 21-item scale that showed high internal consistency (a =.92) and test-retest reliability over 1 week, r(81) =.75. TheBAI discriminated anxious diagnostic groups (panic disorder, general-ized anxiety disorder, etc.) from nonanxious diagnostic groups (major depression, dysthymic disor-der, etc). In addition, the BAI was moderately correlated with the revised Hamilton Anxiety Rating Scale, r(150) =.51, and was only mildly correlated with the revised Hamilton Depression Rating Scale, r(l 53) =.25. Studies addressing the distinctiveness ofanxiety and depres-sion depend on the availability of reliable and valid assessment instruments. However, a number of studies have reported high correlations (r>.50) between the widely used rating scales of anxiety and depression (e.g., Dobson, 1985; Mendels,

We study the question of determining whether an unknown function has a particular property or is ffl-far from any function with that property. A property testing algorithm is given a sample of the value of the function on instances drawn according to some distribution, and possibly may query