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Neural Information Processing Systems

The stochastic multi-armed bandit setting has been recently studied in the nonstationary regime, where the mean payoff of each action is a non-decreasing function of the number of rounds passed since it was last played. This model captures natural behavioral aspects of the users which crucially determine the performance of recommendation platforms, ad placement systems, and more.




Cambridge University wins rowing trademark case

BBC News

The University of Cambridge has won its fight to stop a rowing company based in the city trademarking its name. It argued Cambridge Rowing Limited would be able to take unfair advantage of and cause detriment to the university's reputation if its logo was registered. The university owns trademarks for the word Cambridge, meaning it has the right to stop others from using it in certain circumstances. Omar Terywall, the company's founder, said he was gutted at the outcome and the case had been a terrifying ordeal. He said he hoped to appeal the decision by the Intellectual Property Office (IPO).



EfficientFirst-OrderContextualBandits: Prediction,Allocation,andTriangularDiscrimination

Neural Information Processing Systems

On the technical side, we show that the logarithmic loss and an informationtheoretic quantity called thetriangular discriminationplay a fundamental role in obtaining first-order guarantees, and we combine this observation with new refinements tothe regression oracle reduction framework ofFoster and Rakhlin [29].


Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective

Neural Information Processing Systems

Pedestrian pre-collision pose is one of the key factors to determine the degree of pedestrian-vehicle injury in collision. Human pose estimation algorithm is an effective method to estimate pedestrian emergency pose from accident video.