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» Blind Deconvolution Using the Relative Newton Method
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ICASSP
2011
IEEE
12 years 11 months ago
Application specific loss minimization using gradient boosting
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
CAGD
2004
122views more  CAGD 2004»
13 years 7 months ago
Axioms and variational problems in surface parameterization
For a surface patch on a smooth, two-dimensional surface in IR3 , low-distortion parameterizations are described in terms of minimizers of suitable energy functionals. Appropriate...
Ulrich Clarenz, Nathan Litke, Martin Rumpf
PAMI
2012
11 years 10 months ago
Image Signature: Highlighting Sparse Salient Regions
—We introduce a simple image descriptor referred to as the image signature. We show, within the theoretical framework of sparse signal mixing, that this quantity spatially approx...
Xiaodi Hou, Jonathan Harel, Christof Koch
CIDM
2007
IEEE
13 years 11 months ago
Identifying Anatomical Phrases in Clinical Reports by Shallow Semantic Parsing Methods
Natural Language Processing (NLP) is being applied for several information extraction tasks in the biomedical domain. The unique nature of clinical information requires the need fo...
Vijayaraghavan Bashyam, Ricky K. Taira
IPPS
2007
IEEE
14 years 1 months ago
Replication Strategy in Unstructured Peer-to-Peer Systems
1 The unstructured Peer-to-Peer (P2P) systems usually use a “blind search” method to find the requested data object by propagating a query to a number of peers randomly. In or...
Guofu Feng, Yuquan Jiang, Guihai Chen, Qing Gu, Sa...