Many regression problems exhibit a natural grouping among predictor variables. Examples are groups of dummy variables representing categorical variables, or present and lagged values of time series data. Since model selection in such cases typically aims for selecting groups of variables rather than individual covariates, an extension of the popular least angle regression (LARS) procedure to gr...

Recent work in reinforcement learning has emphasized the power of L1 regularization to perform feature selection and prevent overfitting. We propose formulating theL1 regularized linear fixed point problem as a linear complementarity problem (LCP). This formulation offers several advantages over the LARS-inspired formulation, LARS-TD. The LCP formulation allows the use of efficient off-theshelf...

BACKGROUND Acute bilateral patellar tendon rupture is a rare occurrence, with only 1 case reported in the English literature of a young, fit athlete with no regular medications. To our knowledge this is the first such case reported using a LARS reconstruction. CASE PRESENTATION A 26-year-old otherwise well ex-olympic gymnast with bilateral acute on chronic patellar tendon rupture underwent re...

PURPOSE To report on the use of the Ligament Advanced Reinforcement System (LARS) to enhance joint stability and functional outcome in proximal humeral endoprosthesis reconstruction. METHODS Two men and 5 women aged 16 to 66 (mean, 28) years underwent wide resection of tumour and endoprosthesis reconstruction of the proximal humerus using the LARS, as the rotator cuff and/or deltoid muscle co...

This paper presents a grid-enabled MapReduce framework called “Ussop”. Ussop provides its users with a set of C-language based MapReduce APIs and an efficient runtime system for exploiting the computing resources available on public-resource grids. Considering the volatility nature of the grid environment, Ussop introduces two novel task scheduling algorithms, namely: Variable-Sized Map Schedul...

We would like to thank Philip Lowe, Lars Svensson and David Gruen for helpful suggestions. We are extremely grateful to Luci Ellis for training us in the use of Mathematica 3.0. Any remaining errors are ours. The views expressed are those of the authors and should not be attributed to the Reserve Bank of Australia.

We propose a new algorithm, DASSO, for fitting the entire coefficient path of the Dantzig selector with a similar computational cost to the LARS algorithm that is used to compute the Lasso. DASSO efficiently constructs a piecewise linear path through a sequential simplex-like algorithm, which is remarkably similar to LARS. Comparison of the two algorithms sheds new light on the question of how ...

Classical statistical theory offers validity under restricted assumptions. However, in practice, it is a common approach to perform statistical analysis based on data-driven model selection [1], which guarantees none of results of classical statistical theory. Those results include hypothesis testings and confidence intervals which are useful tools of measuring fitness of models. Considering th...

Ligament reconstruction with the LARS ligament has been a popular choice owing to its low-complication rates compared with previously commercially available grafts. The non-active nature of the implant also meant that there were no foreign body reactions that had been described with other synthetic grafts. We describe the first reported case of a granulomatous foreign body reaction in a LARS li...