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Results 1 - 10
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7,782
Learning with local and global consistency.
- In NIPS,
, 2003
"... Abstract We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised learning is to design a classifying function which is sufficiently smooth with respect to the intr ..."
Abstract
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Cited by 673 (21 self)
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to the intrinsic structure collectively revealed by known labeled and unlabeled points. We present a simple algorithm to obtain such a smooth solution. Our method yields encouraging experimental results on a number of classification problems and demonstrates effective use of unlabeled data.
OPTICS: Ordering Points To Identify the Clustering Structure
, 1999
"... Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all of ..."
Abstract
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Cited by 527 (51 self)
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the intrinsic clustering structure accurately. We introduce a new algorithm for the purpose of cluster analysis which does not produce a clustering of a data set explicitly; but instead creates an augmented ordering of the database representing its density-based clustering structure. This cluster
Laplacian eigenmaps and spectral techniques for embedding and clustering.
- Proceeding of Neural Information Processing Systems,
, 2001
"... Abstract Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami op erator on a manifold , and the connections to the heat equation , we propose a geometrically motivated algorithm for constructing a representation for data sampled from a low dimensional manifold embedded in ..."
Abstract
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Cited by 668 (7 self)
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of the manifold on which the data may possibly reside. Recently, there has been some interest (Tenenbaum et aI, 2000 ; The core algorithm is very simple, has a few local computations and one sparse eigenvalu e problem. The solution reflects th e intrinsic geom etric structure of the manifold. Th e justification
The Contourlet Transform: An Efficient Directional Multiresolution Image Representation
- IEEE TRANSACTIONS ON IMAGE PROCESSING
"... The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” two-dimensional transform that can capture the intrinsic geometrical structure t ..."
Abstract
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Cited by 513 (20 self)
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The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” two-dimensional transform that can capture the intrinsic geometrical structure
Cortical surface-based analysis. I. Segmentation and surface reconstruction
- Neuroimage
, 1999
"... Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical pr ..."
Abstract
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Cited by 450 (42 self)
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Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical
Intrinsic Structural Defects in Monolayer Molybdenum Disulfide
"... ABSTRACT: Monolayer molybdenum disulfide (MoS2) is a two-dimensional direct band gap semiconductor with unique mechan-ical, electronic, optical, and chemical properties that can be utilized for novel nanoelectronics and optoelectronics devices. The performance of these devices strongly depends on th ..."
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on the quality and defect morphology of the MoS2 layers. Here we provide a systematic study of intrinsic structural defects in chemical vapor phase grown monolayer MoS2, including point defects, dislocations, grain boundaries, and edges, via direct atomic resolution imaging, and explore their energy landscape
Learning Object Intrinsic Structure for Robust Visual Tracking
- Proceedings of Int. Conf. on Computer Vision and Pattern Recognition
, 2003
"... In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a low dimensional manifold and can be learned from training data. Based on this assumption, firstly we derived the dimensi ..."
Abstract
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Cited by 28 (0 self)
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In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a low dimensional manifold and can be learned from training data. Based on this assumption, firstly we derived
The Intrinsic Structure of Optic Flow Incorporating Measurement Duality
- International Journal of Computer Vision
, 1997
"... The purpose of this report 1 is to define optic flow for scalar and density images without using a priori knowledge other than its defining conservation principle, and to incorporate measurement duality, notably the scale-space paradigm. It is argued that the design of optic flow based applicati ..."
Abstract
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Cited by 28 (20 self)
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applications may benefit from a manifest separation between factual image structure on the one hand, and goal-specific details and hypotheses about image flow formation on the other. The approach is based on a physical symmetry principle known as gauge invariance. Data-independent models can
Stochastic determination of the intrinsic structure in Bayesian factor analysis
- STATISTICAL AND APPLIED MATHEMATICAL SCIENCES INSTITUTE
, 2004
"... ..."
Chapter 1 Emergence, Intrinsic Structure of Information,
"... Emergence is a central organizing concept for the understanding of complex systems. Under the manifold mathematical notions that have been introduced to characterize emergence, the information-theoretic are of particular interest since they provide a quantitative and transparent approach and general ..."
Abstract
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and generalize beyond the immediate scope at hand. We discuss approaches to characterize emergence using information theory via the intrinsic temporal or compositional structure of the information dynamics of a system. This approach is devoid of any external constraints and purely a property of the information
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