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AAAI
2012
13 years 11 days ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
ICASSP
2011
IEEE
14 years 1 months ago
Worst-case based robust adaptive beamforming for general-rank signal models using positive semi-definite covariance constraint
In this paper, we develop a new approach to the robust beamforming for general-rank signal models. Our method is based on the worst-case performance optimization using a semi-de n...
Haihua Chen, Alex B. Gershman
IPPS
1998
IEEE
15 years 2 months ago
A Mapping Methodology for Designing Software Task Pipelines for Embedded Signal Processing
Abstract. In this paper, we present a methodology for mapping an Embedded Signal Processing ESP application onto HPC platforms such that the throughput performance is maximized. Pr...
Myungho Lee, Wenheng Liu, Viktor K. Prasanna
ICDAR
2003
IEEE
15 years 3 months ago
A Matching Scheme to Enhance Performance Evaluation of Raster-to-Vector Conversion Algorithms
This paper deals with performance evaluation of rasterto-vector conversion algorithms. We briefly review the past work, and focus our attention on a method proposed by Phillips a...
Xavier Hilaire
PAMI
2010
215views more  PAMI 2010»
14 years 8 months ago
Fusion Moves for Markov Random Field Optimization
—The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one p...
Victor S. Lempitsky, Carsten Rother, Stefan Roth, ...