Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets
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Segmenting images is a significant challenge that has drawn a lot of attention from different fields of artificial intelligence and has many practical applications. One such challenge addressed in this thesis is the segmentation of electron microscope (EM) ...
Machine learning is most often cast as an optimization problem. Ideally, one expects a convex objective function to rely on efficient convex optimizers with nice guarantees such as no local optima. Yet, non-convexity is very frequent in practice and it may ...
This paper presents an image-segmentation method which compensates multiplicative distortions based on smooth regularity assumptions. In this work, we generalize the original Chan-Vese functional to handle a continuous multiplicative bias. In the derivati ...
This paper presents an image-segmentation method which compensates multiplicative distortions based on smooth regularity assumptions. In this work, we generalize the original Chan-Vese functional to handle a continuous multiplicative bias. In the derivatio ...
To cope with a variety of clinical applications, research in medical image processing has led to a large spectrum of segmentation techniques that extract anatomical structures from volumetric data acquired with 3D imaging modalities. Despite continuing adv ...
Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained ...
We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a uni ...
We propose a novel method to automatically extract the audio-visual objects that are present in a scene. First, the synchrony between related events in audio and video channels is exploited to identify the possible locations of the sound sources. Video reg ...
Institute of Electrical and Electronics Engineers2012
We present a novel algorithm for the simultaneous segmentation and anatomical labeling of the cerebral vasculature. The method first constructs an over-complete graph capturing the vasculature. It then selects and labels the subset of edges that most likel ...
The design and operating of energy systems are key issues for matching the energy supply and consumption. Several optimization methods based on the Mixed Integer Linear Programming (MILP) have been developed for this purpose. However, due to the uncertaint ...