University of Alberta

About: University of Alberta is a education organization based out in Edmonton, Alberta, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 65403 authors who have published 154847 publications receiving 5358338 citations. The organization is also known as: Ualberta & UAlberta.

The status of the world's land and marine mammals: diversity, threat, and knowledge

Abstract: Knowledge of mammalian diversity is still surprisingly disparate, both regionally and taxonomically. Here, we present a comprehensive assessment of the conservation status and distribution of the world's mammals. Data, compiled by 1700+ experts, cover all 5487 species, including marine mammals. Global macroecological patterns are very different for land and marine species but suggest common mechanisms driving diversity and endemism across systems. Compared with land species, threat levels are higher among marine mammals, driven by different processes (accidental mortality and pollution, rather than habitat loss), and are spatially distinct (peaking in northern oceans, rather than in Southeast Asia). Marine mammals are also disproportionately poorly known. These data are made freely available to support further scientific developments and conservation action.

Natural product synthesis using multicomponent reaction strategies.

Abstract: The preparation of urea by Wöhler constituted a landmark achievement in organic chemistry, and it laid the ground for the early days of target-oriented organic synthesis.1 Since then, significant progress has been achieved in this discipline; many powerful single bond forming reactions and asymmetric variants have been developed. These discoveries have paved the way for the stereoselective assembly of complex organic molecules, a task deemed inconceivable by early practitioners. A great many strategies were invented by chemists in order to facilitate the synthesis of complex natural products.2 One avenue in emulating nature’s efficiency would * To whom correspondence should be addressed. E-mail: dennis.hall@ ualberta.ca. † Novartis Institute for Biomedical Research. ‡ Department of Chemistry, University of Alberta. Chem. Rev. 2009, 109, 4439–4486 4439

Improved Algorithms for Linear Stochastic Bandits

Abstract: We improve the theoretical analysis and empirical performance of algorithms for the stochastic multi-armed bandit problem and the linear stochastic multi-armed bandit problem. In particular, we show that a simple modification of Auer's UCB algorithm (Auer, 2002) achieves with high probability constant regret. More importantly, we modify and, consequently, improve the analysis of the algorithm for the for linear stochastic bandit problem studied by Auer (2002), Dani et al. (2008), Rusmevichientong and Tsitsiklis (2010), Li et al. (2010). Our modification improves the regret bound by a logarithmic factor, though experiments show a vast improvement. In both cases, the improvement stems from the construction of smaller confidence sets. For their construction we use a novel tail inequality for vector-valued martingales.