Yahoo!

About: Yahoo! is a company organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Web search query. The organization has 26749 authors who have published 29915 publications receiving 732583 citations. The organization is also known as: Yahoo! Inc. & Maudwen-Yahoo! Inc.

A modified technique for descemet membrane stripping automated endothelial keratoplasty to minimize endothelial cell loss.

Abstract: In an attempt to enhance postoperative survival of donor endothelium, the conventional technique for Descemet membrane stripping automated endothelial keratoplasty (DSAEK) was modified using the prototype of a glide specially designed to facilitate graft delivery and minimize surgical trauma Instead of using the so-called taco technique, the Busin glide is loaded with the donor lamella, and a microincision forceps is inserted into a temporal side entry and passed across the anterior chamber, exiting through a nasal clear cornea tunnel to grab the graft and drag it into the eye In 10 patients who underwent DSAEK, mean (SD) postoperative endothelial cell loss was 200% (26%) at 6 months, 235% (28%) at 12 months, and 264% (27%) at 18 to 24 months Reduced trauma to the graft using our modified technique limits endothelial cell loss after DSAEK to the level recorded after conventional penetrating keratoplasty (PK)

Simple and Deterministic Matrix Sketching

Abstract: We adapt a well known streaming algorithm for approximating item frequencies to the matrix sketching setting. The algorithm receives the rows of a large matrix $A \in \R^{n \times m}$ one after the other in a streaming fashion. It maintains a sketch matrix $B \in \R^ {1/\eps \times m}$ such that for any unit vector $x$ [\|Ax\|^2 \ge \|Bx\|^2 \ge \|Ax\|^2 - \eps \|A\|_{f}^2 \.] Sketch updates per row in $A$ require $O(m/\eps^2)$ operations in the worst case. A slight modification of the algorithm allows for an amortized update time of $O(m/\eps)$ operations per row. The presented algorithm stands out in that it is: deterministic, simple to implement, and elementary to prove. It also experimentally produces more accurate sketches than widely used approaches while still being computationally competitive.

OrdRec: an ordinal model for predicting personalized item rating distributions

Abstract: We propose a collaborative filtering (CF) recommendation framework, which is based on viewing user feedback on products as ordinal, rather than the more common numerical view. This way, we do not need to interpret each user feedback value as a number, but only rely on the more relaxed assumption of having an order among the different feedback ratings. Such an ordinal view frequently provides a more natural reflection of the user intention when providing qualitative ratings, allowing users to have different internal scoring scales. Moreover, we can address scenarios where assigning numerical scores to different types of user feedback would not be easy. Our approach is based on a pointwise ordinal model, which allows it to linearly scale with data size. The framework can wrap most collaborative filtering algorithms, upgrading those algorithms designed to handle numerical values into being able to handle ordinal values. In particular, we demonstrate our framework with wrapping a leading matrix factorization CF method. A cornerstone of our method is its ability to predict a full probability distribution of the expected item ratings, rather than only a single score for an item. One of the advantages this brings is a novel approach to estimating the confidence level in each individual prediction. Compared to previous approaches to confidence estimation, ours is more principled and empirically superior in its accuracy. We demonstrate the efficacy of the approach on some of the largest publicly available datasets, the Netflix data, and the Yahoo! Music data.

Effects of in-season short-term plyometric training program on leg power, jump- and sprint performance of soccer players.

Abstract: Our hypothesis was that the addition of an 8-week lower limb plyometric training program (hurdle and depth jumping) to normal in-season conditioning would enhance measures of competitive potential (peak power output [PP], jump force, jump height, and lower limb muscle volume) in junior soccer players. The subjects (23 men, age 19 ± 0.7 years, body mass 70.5 ± 4.7 kg, height 1.75 ± 0.06 m, body fat 14.7 ± 2.6%) were randomly assigned to a control (normal training) group (Gc; n = 11) and an experimental group (Gex, n = 12) that also performed biweekly plyometric training. A force-velocity ergometer test determined PP. Characteristics of the squat jump (SJ) and the countermovement jump (CMJ) (jump height, maximal force and velocity before take-off, and average power) were determined by force platform. Video-camera kinematic analyses over a 40-m sprint yielded running velocities for the first step (VS), the first 5 m (V5m) and between 35 and 40 m (Vmax). Leg muscle volume was estimated using a standard anthropometric kit. Gex showed gains relative to controls in PP (p < 0.01); SJ (height p < 0.01; velocity p < 0.001), CMJ (height p < 0.001; velocity p < 0.001, average power p < 0.01) and all sprint velocities (p < 0.001 for V5m and Vmax, p < 0.01 for VS). There was also a significant increase (p < 0.05) in thigh muscle volume, but leg muscle volume and mean thigh cross-sectional area remain unchanged. We conclude that biweekly plyometric training of junior soccer players (including adapted hurdle and depth jumps) improved important components of athletic performance relative to standard in-season training. Accordingly, such exercises are highly recommended as part of an annual soccer training program.

Comparative usability evaluation

Abstract: This paper reports on a study assessing the consistency of usability testing across organisations. Nine independent organisations evaluated the usability of the same website, Microsoft Hotmail. The results document a wide difference in selection and application of methodology, resources applied, and problems reported. The organizations reported 310 different usability problems. Only two problems were reported by six or more organizations, while 232 problems (75%) were uniquely reported, that is, no two teams reported the same problem. Some of the unique findings were classified as serious. Even the tasks used by most or all teams produced very different results - around 70% of the findings for each of these tasks were unique. Our main conclusion is that our simple assumption that we are all doing the same and getting the same results in a usability test is plainly wrong.