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.

Beyond the regret minimization barrier: optimal algorithms for stochastic strongly-convex optimization

Abstract: We give novel algorithms for stochastic strongly-convex optimization in the gradient oracle model which return a O(1/T)-approximate solution after T iterations. The first algorithm is deterministic, and achieves this rate via gradient updates and historical averaging. The second algorithm is randomized, and is based on pure gradient steps with a random step size. his rate of convergence is optimal in the gradient oracle model. This improves upon the previously known best rate of O(log(T/T), which was obtained by applying an online strongly-convex optimization algorithm with regret O(log(T)) to the batch setting. We complement this result by proving that any algorithm has expected regret of Ω(log(T)) in the online stochastic strongly-convex optimization setting. This shows that any online-to-batch conversion is inherently suboptimal for stochastic strongly-convex optimization. This is the first formal evidence that online convex optimization is strictly more difficult than batch stochastic convex optimization.

Sponsored search: A brief history

Abstract: La recherche sponsorisee sur le Web, qui permet aux annonceurs de faire apparaitre leurs contenus dans les resultats affiches par un moteur de recherche, a demarre en 1998 avec GoTo, acquis par Yahoo! en 2002. Le prix de l'apparition sur un site donne peut etre fonction du nombre d'apparitions (cout pour mille), des clicks sur un lien (cout par click) ou des actes engendres (cout par action). La recherche payee souleve un interet grandissant au sein de la communaute academique.

Trust propagation through both explicit and implicit social networks

Abstract: The present invention is directed towards systems and methods for trust propagation. The method according to one embodiment comprises calculating a first feature vector for a first user, calculating a second feature for a second user and comparing the first feature vector with the second feature vector to calculate a similarity value. A determination is made as to whether the similarity value falls within a threshold. If the similarity value falls within the threshold, a relationship is recorded between the first user and the second user in a first user profile and a second user profile.

Hypertension in mice lacking the proatrial natriuretic peptide convertase corin

Abstract: Atrial natriuretic peptide (ANP) is a cardiac hormone that regulates blood pressure. In cardiomyocytes, the hormone is synthesized as a precursor, proatrial natriuretic peptide (pro-ANP), which is proteolytically converted to active ANP. Corin is a cardiac transmembrane serine protease that has been shown to process pro-ANP in vitro, but its physiological importance had not been established. Here, we show that corin-deficient (Cor-/-) mice develop normally during embryogenesis and survive to postnatal life. Cor-/- mice have elevated levels of pro-ANP but no detectable levels of ANP as compared with WT littermates. Infusion of an active recombinant soluble corin transiently restores pro-ANP conversion, resulting in the release of circulating biologically active ANP. Using radiotelemetry to assess blood pressure, we find that Cor-/- mice have spontaneous hypertension as compared with WT mice, and it is enhanced after dietary salt loading. Pregnant Cor-/- mice demonstrate late-gestation proteinuria and enhanced high blood pressure during pregnancy. In addition, Cor-/- mice exhibit cardiac hypertrophy resulting in a mild decline in cardiac function later in life. Thus, our data establish corin as the physiological pro-ANP convertase and indicate that corin deficiency may contribute to hypertensive heart disease.

Systems and methods for inserting ads during playback of video media

Abstract: The solution of the ad delivery platform described herein provides for the marketing and monetizing of media assets via the delivery of advertisement with on-demand video. The ad platform optimizes the delivery of ads by controlling the insertion frequency and format of the ad delivered with video streams. The ad platform provides flexible and configurable ad insertion rules to specify the insertion frequency and format for the composition of ads during playback of on-demand video media. The ad insertion rules may be based on a user profile, user behavior history, topic of the stream to be delivered, duration of the video or ad, and/or the popularity rating of the video or ad. The ad platform includes a reporting tool and usage reports to measure the effectiveness of the ad insertion rules in delivering ads to market and monetize the video media. The ad platform also includes an ad inventory management and forecasting tool for determining the available inventory of ad placement based on data collected over a period of time regarding the delivery of ads and the ad insertion rules to be used for the delivery of a desired ad. With these tools, a more effective ad campaign can be created based on the target information and optimization via the ad insertion rules.