Abstract: A method, an apparatus, and a computer readable medium of recommending contents. The method includes receiving, by a computer, at least one of user input and contextual input, wherein the contextual input corresponds to a plurality of arms, calculating, by the computer, a plurality of reward values for each of the plurality of arms using a plurality of individual recommendation algorithms such that each of the plurality of reward values is generated by a respective individual recommendation algorithm from the plurality of individual recommendation algorithms, based on the received input, calculating, by the computer, an aggregated reward value for each of the plurality of arms by applying linear program boosting to the plurality reward values for the respective arm; and selecting one arm from the plurality of arms which has greatest calculated aggregated reward value; and outputting, by the computer, contents corresponding to the selected arm.

Abstract: A method, an apparatus, and a computer readable medium of recommending contents. The method includes receiving, by a computer, at least one of user input and contextual input, wherein the contextual input corresponds to a plurality of arms, calculating, by the computer, a plurality of reward values for each of the plurality of arms using a plurality of individual recommendation algorithms such that each of the plurality of reward values is generated by a respective individual recommendation algorithm from the plurality of individual recommendation algorithms, based on the received input, calculating, by the computer, an aggregated reward value for each of the plurality of arms by applying linear program boosting to the plurality reward values for the respective arm; and selecting one arm from the plurality of arms which has greatest calculated aggregated reward value; and outputting, by the computer, contents corresponding to the selected arm.

Abstract: Embodiments of the invention provide systems and methods for fair share allocation of inventory levels throughout a supply chain. According to one embodiment, a first round main Linear Programming (LP) solve can generate an initial solution. Post-processing heuristics for fair sharing can be applied to the first round solve of the main LP. Circular sourcing heuristics can be applied to the first round solve when adjusting for fair sharing allocation requirements. For example, applying the circular sourcing heuristics to the first round solve of the main LP can comprise determining a firmed supply surplus and shortage based on a demand picture from the first round solve of the main LP adjusted for fair sharing. A second round main LP solve can be executed using the fixed inter-organizational transfer variables and fixed supply towards independent demand variables from the post-processing heuristics.