Abstra t Most lassi ation algorithms experien e diÆ ulties when the input-output distribution is irregular (i.e., neighbor examples in the input spa e have di erent values in the output spa e), and sparse. We hara terize the diÆ ulty of a lassi ation problem using a limited number of examples by re-de ning a measure of lass variation to a ount for irregular distributions, and by introdu ing a n...

Since the papers of Basu et. al. (1985) and Lal and Srinivasan (1993), marketing academics have been interested in the design and implementation of optimal compensation plans. The literature has focused on agency theory as a foundation to help describe and understand this process. Although there has been much theoretical work on this topic, empirical evidence to support this theory remains spar...

This paper identifies and analyzes the long-term rising trend in single-family mortgage foreclosure rates. Traditional measures of mortgage risk, such as house appreciation rates and loan-to-value ratios (LTVs), appear to explain some, but not all, of the long-term trend. In an effort to explain the remaining part of the trend, several non-traditional hypotheses are explored. One is the notion ...

We study the recovery of sparse signals from underdetermined linear measurements when a potentially erroneous support estimate is available. Our results are twofold. First, we derive necessary and sufficient conditions for signal recovery from compressively sampled measurements using weighted l1norm minimization. These conditions, which depend on the choice of weights as well as the size and ac...

In this paper, we are concerned with regression problems where covariates can be grouped in nonoverlapping blocks, and where only a few of them are assumed to be active. In such a situation, the group Lasso is an attractive method for variable selection since it promotes sparsity of the groups. We study the sensitivity of any group Lasso solution to the observations and provide its precise loca...

In this paper we study the differentially private Empirical Risk Minimization (ERM) problem in different settings. For smooth (strongly) convex loss function with or without (non)-smooth regularization, we give algorithms that achieve either optimal or near optimal utility bounds with less gradient complexity compared with previous work. For ERM with smooth convex loss function in high-dimensio...

The representer theorem assures that kernel methods retain optimality under penalized empirical risk minimization. While a sufficient condition on the form of the regularizer guaranteeing the representer theorem has been known since the initial development of kernel methods, necessary conditions have only been investigated recently. In this paper we completely characterize the necessary and suf...

A bout 218,890 new prostate cancer diagnoses were expected in the United States during 2007, with 27,050 men dying of the disease. Men have a 17 percent lifetime risk of prostate cancer, but only a 3 percent risk of dying from the disease. Black men have the highest incidence of prostate cancer in the world. The age-adjusted death rate from prostate cancer is 64.4 per 100,000 for black men comp...

In this paper, we study the dividend payments prior to absolute ruin in a Markov-dependent risk process in which the claim occurrence and the claim amount are regulated by an external discrete time Markov chain. A system of integrodifferential equations with boundary conditions satisfied by the moment-generating function, the nth moment of the discounted dividend payments prior to absolute ruin...

REVIEW ARTICLE Determinative Factors in The Injury Incidence on Runners: Synthesis of Evidence “Injuries on Runners” Andrigo Zaar, Eduardo Borba Neves, Abel Ilah Rouboa and Victor Machado Reis Department of Physical Education of João Pessoa University Center (UNIPÊ) João Pessoa, Paraíba, Brazil Kinanthropometry and Human Development Laboratory (UFPB), João Pessoa, Paraíba, Brazil Brazilian Army...