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78
Information geometry of U-Boost and Bregman divergence
- Neural Computation
, 2004
"... We aim to extend from AdaBoost to U-Boost in the paradigm to build up a stronger classification machine in a set of weak learning machines. A geometric understanding for the Bregman divergence defined by a generic function U being convex leads to U-Boost method in the framework of information geomet ..."
Abstract
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Cited by 32 (9 self)
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geometry for the finite measure functions over the label set. We propose two versions of U-Boost learning algorithms by taking whether the domain is restricted to the space of probability functions or not. In the sequential step we observe that the two adjacent and the initial classifiers associate with a
An Information Fusion Framework for Robust Shape Tracking
, 2005
"... Existing methods for incorporating subspace model constraints in shape tracking use only partial information from the measurements and model distribution. We propose a unified framework for robust shape tracking, optimally fusing heteroscedastic uncertainties or noise from measurement, system dynam ..."
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Cited by 50 (9 self)
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build shape models offline from training data and exploit information from the ground truth initialization online through a strong model adaptation. Our framework is applied for tracking in echocardiograms where the motion estimation errors are heteroscedastic in nature, each heart has a distinct shape
LETTER Communicated by Shun-ichi Amari Information Geometry of U-Boost and Bregman Divergence
"... We aim at an extension of AdaBoost to U-Boost, in the paradigm to build a stronger classification machine from a set of weak learning machines. A geometric understanding of the Bregman divergence defined by a generic convex function U leads to the U-Boost method in the framework of in-formation geom ..."
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geometry extended to the space of the finite measures over a label set. We propose two versions of U-Boost learning algorithms by taking account of whether the domain is restricted to the space of proba-bility functions. In the sequential step, we observe that the two adjacent and the initial classifiers
Pigeons’ (Columba livia) encoding of geometric and featural properties of a spatial environment
- Journal of Comparative Psychology
, 1998
"... Pigeons (Columba livia) searched for hidden food in a rectangular environment constructed to eliminate xternal orientation cues. A feature group was initially trained with distinct features in each corner. A geometric group was initially trained with no featural information. Tests revealed that both ..."
Abstract
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Cited by 42 (5 self)
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Pigeons (Columba livia) searched for hidden food in a rectangular environment constructed to eliminate xternal orientation cues. A feature group was initially trained with distinct features in each corner. A geometric group was initially trained with no featural information. Tests revealed
Synthesizing Oil Painting Surface Geometry from a Single Photograph
"... We present an approach to synthesize the subtle 3D re-lief and texture of oil painting brush strokes from a single photograph. This task is unique from traditional synthesize algorithms due to its mixed modality between the input and output; i.e., our goal is to synthesize surface normals given an i ..."
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an intensity image input. To accomplish this task, we pro-pose a framework that first applies intrinsic image decom-position to produce a pair of initial normal maps. These maps are combined into a conditional random field (CR-F) optimization framework that incorporates additional in-formation derived from a
Spike train metrics Theoretical background
"... Quantifying similarity and dissimilarity of spike trains is an important requisite for understanding neural codes. Spike metrics constitute a class of approaches to this problem. In contrast to most signal-processing methods, spike metrics operate on time series of all-or-none events, and are, thus ..."
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be more expensive than an itinerary that is constrained to stop at B. It is easy to construct examples of metrics that violate the rules of Euclidean geometry. Cost-based metrics for spike trains With some fine print, Equation 1 provides a way to turn any set of (symmetric) costs into a metric
Transfer of Training: A Meta-Analytic Review On behalf of: Southern Management Association can be found at: Journal of Management Additional services and information for Transfer of Training: A Meta-Analytic Review
"... Although transfer of learning was among the very first issues addressed by early psychologists, the extant literature remains characterized by inconsistent measurement of transfer and significant variability in findings. This article presents a meta-analysis of 89 empirical studies that explore the ..."
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much of the initial interest in transfer focused on understanding educational issues, such as how learning in one domain might affect learning in another Transfer Research As noted by Brown and Sitzmann (in press), the most frequently cited model of training transfer is one presented by The goal
Unsupervised Eye Pupil Localization through Differential Geometry and Local Self-Similarity Matching
"... The automatic detection and tracking of human eyes and, in particular, the precise localization of their centers (pupils), is a widely debated topic in the international scientific community. In fact, the extracted information can be effectively used in a large number of applications ranging from ad ..."
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Cited by 1 (0 self)
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challenging operating conditions is still an open scientific topic in Computer Vision. Actually, the most performing solutions in the literature are, unfortunately, based on supervised machine learning algorithms which require initial sessions to set the working parameters and to train the embedded learning
ViVa: The Virtual Vascular Project
"... The aim of the ViVa project is to develop tools for the modern hemodynamicist and cardiovascular surgeon to study and interpret the constantly increasing amount of information being produced by non--invasive imaging equipment. In particular, we are developing a system able to process and visualize 3 ..."
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Cited by 8 (1 self)
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3D medical data, to reconstruct the geometry of arteries of specific patients and to simulate blood flow in them. The initial applications of the system will be for clinical research and training purposes. In a later stage we will explore the application of the system to surgical planning. Vi
BETA CAE Systems S.A.
"... Abstract—In this paper we propose a novel dimensionality reduction method that is based on successive Laplacian SVM pro-jections in orthogonal deflated subspaces. The proposed method, called Laplacian Support Vector Analysis, produces projection vectors, which capture the discriminant information th ..."
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that lies in the subspace orthogonal to the standard Laplacian SVMs. We show that the optimal vectors on these deflated subspaces can be computed by successively training a standard SVM with specially designed deflation kernels. The resulting normal vectors contain discriminative information that can
Results 1 - 10
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78
