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Large Margin Methods for Structured and Interdependent Output Variables
Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainlyExpand
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  • Open Access
Probabilistic latent semantic indexing
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a trainingExpand
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Support Vector Machines for Multiple-Instance Learning
This paper presents two new formulations of multiple-instance learning as a maximum margin problem. The proposed extensions of the Support Vector Machine (SVM) learning approach lead to mixed integerExpand
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  • Open Access
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input representations.Expand
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  • Open Access
Unsupervised Learning by Probabilistic Latent Semantic Analysis
This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a technique known as Latent Semantic Analysis. In contrast to the latter methodExpand
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Probabilistic Latent Semantic Analysis
Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two-mode and co-occurrence data, which has applications in information retrieval and filtering, naturalExpand
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  • Open Access
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines and Hidden MarkovExpand
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Latent semantic models for collaborative filtering
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, that is, a database of available user preferences. In this article, weExpand
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Beyond sliding windows: Object localization by efficient subwindow search
Most successful object recognition systems rely on binary classification, deciding only if an object is present or not, but not providing information on the actual object location. To performExpand
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Probabilistic Latent Semantic Indexing
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a trainingExpand
  • 1,143
  • 71
  • Open Access