Esophageal adenocarcinoma arises from Barrett’s esophagus, which is the most serious complication of gastroesophageal reflux disease. Strategies for screening involve periodic surveillance and tissue biopsies. A major challenge in such regular examinations is to record and track the disease evolution and re-localization of biopsied sites to provide targeted treatments. In this paper, we extend ...

Sexual selection is a major force driving the evolution of diverse reproductive traits. This evolutionary process is based on individual reproductive advantages that arise either through intrasexual competition or through intersexual choice and conflict. While classical studies of sexual selection focused mainly on differences in male mating success, more recent work has focused on the differen...

In this paper, we unify causal and non-causal feature selection methods based on the Bayesian network framework. We first show that the objectives of causal and non-causal feature selection methods are equal and are to find the Markov blanket of a class attribute, the theoretically optimal feature set for classification. We demonstrate that causal and non-causal feature selection take different...

Multi-body structure-and-motion (MSaM) is the problem to establish the multiple-view geometry of an image sequence of a 3D scene, where the scene consists of multiple rigid objects moving relative to each other. So far, solutions have been proposed for several restricted settings, such as only two views, affine projection, and perspective projection of linearly moving points. We give a solution...

Adaptive action selection is crucial for object recognition on robots with limited operating capabilities. It offers much desired flexibility in trading off between the costs of acquiring information and making robust and reliable inference under uncertainty. In this paper, we describe an information-theoretic framework that combines and unifies two common techniques: view planning for resolvin...

Object recognition accuracy can be improved when information from multiple views is integrated, but information in each view can often be highly redundant. We consider the problem of distributed object recognition or indexing from multiple cameras, where the computational power available at each camera sensor is limited and communication between sensors is prohibitively expensive. In this scena...

This paper presents a method for solving the Best Next View problem. This problem arises while gathering range data for the purpose of building 3D models of objects. The novelty of our solution is the introduction of a quality criterion in addition to the visibility criterion used by previous researchers. This quality criterion aims at obtaining views that improve the overall range data quality...

Materialized view selection is a non-trivial task. Hence, its complexity must be reduced. A judicious choice of views must be costdriven and influenced by the workload experienced by the system. In this paper, we propose a framework for materialized view selection that exploits a data mining technique (clustering), in order to determine clusters of similar queries. We also propose a view mergin...

Living systems are subject to constant evolution. The environment can be considered as a nutriment shared by all the population. This alllows certain individuals, charaterized by a ’trait’ to better develop but also to change the environment. This leads to select the ’best adapted trait’ in the population. On the other hand the population can develop with small variance on the trait (mutations)...

In the past decade, social and information networks have become prevalent, and research on the network data has attracted much attention. Besides the link structure, network data are often equipped with the content information (i.e, node attributes) that is usually noisy and characterized by high dimensionality. As the curse of dimensionality could hamper the performance of many machine learnin...