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This paper suggests a method for multiclass learning with many classes by simultaneously learning shared characteristics common to the classes, and predictors for the classes in terms of these characteristics. We cast this as a convex optimization problem, using <i>trace-norm</i> regularization and study gradient-based optimization both for the linear case(More)
Mutual Boosting is a method aimed at incorporating contextual information to augment object detection. When multiple detectors of objects and parts are trained in parallel using AdaBoost [1], object detectors might use the remaining intermediate detectors to enrich the weak learner set. This method generalizes the efficient features suggested by Viola and(More)
We describe a general framework for online multiclass learning based on the notion of hypothesis sharing. In our framework sets of classes are associated with hypotheses. Thus, all classes within a given set share the same hypothesis. This framework includes as special cases commonly used constructions for multiclass categorization such as allocating a(More)
Baeyer–Villiger monooxygenase-catalysed reactions are attractive for industrial processes. Here we report on expanding the substrate scope of phenylacetone monooxygenase (PAMO). In order to introduce activity on alicyclic ketones in PAMO, we generated and screened a library of 1,500 mutants. Based on recently published structures of PAMO and its mutants, we(More)
In this paper, we propose a method for detecting and precisely segmenting repeated sections of broadcast streams. This method allows advertisements to be removed and replaced with new ads in redistributed television material. The detection stage starts from acoustic matches and validates the hypothesized matches using the visual channel. Finally, the(More)
This paper describes mass personalization, a framework for combining mass media with a highly personalized Web-based experience. We introduce four applications for mass personalization: personalized content layers, ad hoc social communities, real-time popularity ratings and virtual media library services. Using the ambient audio originating from the(More)
We describe the image collection and labeling procedures of an office scene database. The office database is aimed at providing training and benchmarking tools for multiclass object detection in natural scenes. The described database is unique in the fact that high quality office images were collected following a protocol that (in theory) does not introduce(More)
A new technique provides accurate, efficient ad detection for online TV rebroadcasts. As online television grows in popularity, providers are seeking cost-effective ways to replace original advertisements in rebroadcasts with new ads that are not only fresher but that can target individual viewers' interests and preferences. Alternatively, completely(More)