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Learning the Kernel Matrix with Semidefinite Programming
TLDR
Kernel-based learning algorithms work by embedding the data into a Euclidean space and then searching for linear relations among the embedded data points. Expand
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A new approach to cross-modal multimedia retrieval
TLDR
The problem of joint modeling the text and image components of multimedia documents is studied. Expand
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Multiple kernel learning, conic duality, and the SMO algorithm
TLDR
We propose a novel dual formulation of the QCQP as a second-order cone programming problem, and show how to exploit the technique of Moreau-Yosida regularization to yield a formulation to which SMO techniques can be applied. Expand
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A Robust Minimax Approach to Classification
TLDR
We show how to exploit Mercer kernels in this setting to obtain nonlinear decision boundaries, yielding a classifier which proves to be competitive with current methods, including support vector machines. Expand
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Semantic Annotation and Retrieval of Music and Sound Effects
TLDR
We present a computer audition system that can both annotate novel audio tracks with semantically meaningful words and retrieve relevant tracks from a database of unlabeled audio content given a text-based query. Expand
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A Direct Formulation for Sparse PCA Using Semidefinite Programming
TLDR
We use a modification of the classical variational representation of the largest eigenvalue of a symmetric matrix, where cardinality is constrained, and derive a semidefinite programming-based relaxation for the sparse PCA problem. Expand
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A Direct Formulation for Sparse Pca Using Semidefinite Programming
We examine the problem of approximating, in the Frobenius-norm sense, a positive, semidefinite symmetric matrix by a rank-one matrix, with an upper bound on the cardinality of its eigenvector. TheExpand
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A statistical framework for genomic data fusion
TLDR
This paper presents a computational and statistical framework for integrating and drawing inferences from a collection of genome-wide measurements. Expand
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On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval
TLDR
The problem of cross-modal retrieval from multimedia repositories is considered. Expand
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Hilbert Space Embeddings and Metrics on Probability Measures
TLDR
A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing, and independence testing. Expand
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