2,965 research outputs found

    Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

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    We study contextual linear bandit problems under uncertainty on features; they are noisy with missing entries. To address the challenges from the noise, we analyze Bayesian oracles given observed noisy features. Our Bayesian analysis finds that the optimal hypothesis can be far from the underlying realizability function, depending on noise characteristics, which is highly non-intuitive and does not occur for classical noiseless setups. This implies that classical approaches cannot guarantee a non-trivial regret bound. We thus propose an algorithm aiming at the Bayesian oracle from observed information under this model, achieving O~(dT)\tilde{O}(d\sqrt{T}) regret bound with respect to feature dimension dd and time horizon TT. We demonstrate the proposed algorithm using synthetic and real-world datasets.Comment: 30 page

    Free radical-catalyzed synthesis of benzoprostacyclins

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    A method is provided for preparing benzoprostacyclins by the free-radical-catalyzed tandem alkene insertion into a 1,4-bisoxy-substituted cyclopent-2-ene intermediate

    Synthesis of benzoprostacyclins using palladium catalysis

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    A method is provided for preparing benzoprostacyclins by the palladium-catalyzed tandem alkene insertion into a 1,4-bisoxy-substituted cyclopent-2-ene intermediate

    Fostering the Growth of the Social Impact Business sector in Viet Nam

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    “Fostering the Growth of the Social Impact Business Sector in Viet Nam” (the “study”) is the largest study on the social impact business (SIB) sector in Viet Nam undertaken to date. Findings are taken from 492 survey responses, interviews with 62 individuals representing various stakeholder groups, through one-on-one interviews or focus groups, and three multi-stakeholder consultative workshops. The study provides an overview of the ecosystem and the current state of the SIB sector in Viet Nam, together with challenges and opportunities, to produce key recommendations to grow the sector. Practical guidance targeted at SIBs in growing their enterprise is also included to share the advices and insights taken from consultation with SIB sector leaders. The main objective of the study is to catalyse the development of business activities toward addressing pressing social and environmental challenges, and ultimately toward the achievement of the UN Sustainable Development Goals (SDGs)1. The study was conducted in the context where there is a need to map the SIB sector in Viet Nam, which is recognised as an invaluable driver for positive social and environmental change, in order to design interventions to support the Government of Viet Nam in achieving the SDGs by 2030. The study aims to apply a wider understanding of the SIB sector to map and understand the huge potential of the sector from across a varied spectrum of organisations and models, all connected by their mission to solve social or environmental issues. For the purposes of the study, SIBs are understood as “organisations that have both trading activities and a commitment to positively impacting society/environment as the two central tenets of their strategic operations. This balancing of their social/environmental aims with a commercial model allows them to sustainably solve social and environmental challenges.”. This sector may include non-profit organisations having commercial activities, legally registered Social Enterprises (SEs), cooperatives, inclusive businesses, social impact startups, and commercial enterprises for sustainable development. SIB in this study is therefore provided as a working definition, one that seeks to respond to the concerns and barriers facing business leaders who have integrated social missions into their business models, and hence foster further growth of the wider SIB sector in Viet Nam
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