Learn More
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)
Computational models of cardiac electrophysiology are exemplar demonstrations of the integration of multiple data sets into a consistent biophysical framework. These models encapsulate physiological understanding to provide quantitative predictions of function. The combination or extension of existing models within a common framework allows integrative(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)
The technical part of these Guidelines and Recommendations, produced under the auspices of EFSUMB, provides an introduction to the physical principles and technology on which all forms of current commercially available ultrasound elastography are based. A difference in shear modulus is the common underlying physical mechanism that provides tissue contrast(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)
Different notions of equivalence, such as the prominent notions of strong and uniform equivalence, have been studied in Answer-Set Programming, mainly for the purpose of identifying programs that can serve as substitutes without altering the semantics, for instance in program optimization. Such semantic comparisons are usually characterized by various(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)
Cardiac experimental electrophysiology is in need of a well-defined Minimum Information Standard for recording, annotating, and reporting experimental data. As a step towards establishing this, we present a draft standard, called Minimum Information about a Cardiac Electrophysiology Experiment (MICEE). The ultimate goal is to develop a useful tool for(More)