multi-instance learning
A Review of Multi-Instance Learning Assumptions
... Abstract Multi-instance (MI) learning is a variant of inductive machine learning where each learning example contains a bag of instances instead of a single feature ...real-world ...
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Avoiding False Positive in Multi-Instance Learning
... yanjun.han, qing.tao, [email protected] Abstract In multi-instance learning, there are two kinds of prediction failure, i.e., false negative and false positive. Current research mainly focus on ...
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Multi-Instance Learning with Any Hypothesis Class
... It is possible, in principle, to view MIL as a regular supervised classification task, where a bag is a single example, and the instances in a bag are merely part of its internal representation. Such a view, however, ...
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Multi-view multi-instance learning based on joint sparse representation and multi-view dictionary learning
... Abstract—In multi-instance learning (MIL), the relations among instances in a bag convey important contextual information in many ...novel multi-view multi-instance ...
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Multi view multi instance learning based on joint sparse representation and multi view dictionary learning
... Abstract—In multi-instance learning (MIL), the relations among instances in a bag convey important contextual information in many ...novel multi-view multi-instance ...
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A Novel Automatic Image Annotation Method Based on Multi-Instance Learning
... of Multi-instance Learning In the previous learning framework, a sample is viewed as an instance, ...of multi-instance learning differ from ones of supervised ...
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Horror image recognition based on context aware multi instance learning
... 2 School of Computer Science and Information Systems, Birkbeck College, UK 3 Department of ECE, National University of Singapore, Singapore (*Corresponding Author: [email protected]) Abstract Horror content sharing on ...
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Multi-instance Learning for Bipolar Disorder Diagnosis using Weakly Labelled Speech Data
... deep learning is undoubtedly the predominant learning tech- nique across speech processing, it is still not widely used in health- based ...a multi-instance learning framework aimed at ...
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The Impact of Missing Labels and Overlapping Sound Events on Multi-label Multi-instance Learning for Sound Event Classification
... of learning sound event classifier models by a set of exam- ple sound segments that contain multiple potentially overlapping sound events and that are labeled with multiple weak sound event class ...both ...
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Latent topic based multi-instance learning method for localized content-based image retrieval
... the instance labels were unavailable, these multi-instance kernels implicitly assumed that all instances in a bag be equally ...single instance learning (SIL) methods ...], ...
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Dimension Reduction and Classification of Hyperspectral Images based on Neural Network Sensitivity Analysis and Multi-instance Learning
... and Multi-instance Learning 453 ...on Multi- instance Learning As described above, in multi-instance learning [31–32], the training set is composed of ...
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A review of multi-instance learning assumptions
... Abstract Multi-instance (MI) learning is a variant of inductive machine learning, where each learning example contains a bag of instances instead of a single feature ...real-world ...
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A meta-learning system for multi-instance classification
... generalized multi-instance setting, as there is no assumption about the existence of instance ...the multi-instance ...supervised learning, AdaBoost is prone to overfitting on ...
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Applying propositional learning algorithms to multi-instance data
... into multi-instance learning algorithms that are specifically designed to deal with bags of ...propositional learning algorithms when it comes to tackling multi-instance ...
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Multi-View Multi-Instance Multi-Label Learning Based on Collaborative Matrix Factorization
... a multi-view multi-instance learning algorithm (M 2 IL), which generates different graphs with different parameters to represent various contextual re- lations between instances of a ...and ...
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Automated skin biopsy histopathological image annotation using multi-instance representation and learning
... base multi-instance learning assumptions [24] for our task, we build model from the original assump- tion ...Bayesian learning to the multi-instance setting and model the ...
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Predicting multiple functions of sustainable flood retention basins under uncertainty via multi instance multi label learning
... the multi-instance or multi-label frameworks cannot capture all real-world ...of multi-instance learning and multi-label learning, which is called a ...
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Multi-instance multi-label learning
... supervised learning, an object is represented by an instance, ...the instance space (or feature space) and Y the set of class ...an instance and y i ∈ Y is the known label of x i ...
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Multi instance Multi label Learning for Relation Extraction
... ing learning scenario where the relation ex- pressed by a pair of entities found in a sen- tence is ...vised learning, which assumes that each ex- ample is explicitly mapped to a label, is not ...to ...
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Multi-instance multi-label learning in the presence of novel class instances
... Multi-instance multi-label learning (MIML) is a framework for learning in the presence of label ...an instance-level classifier for all classes including the novel ...
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