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Co-EM support vector learning

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4757-2440-0openalex-snapshot

The Nature of Statistical Learning Theory

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Learning from Labeled and Unlabeled Data

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Using Transduction and Multi-view Learning to Answer Emails

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Support Vector Machines with Example Dependent Costs

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The use of the area under the ROC curve in the evaluation of machine learning algorithms

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Text Classification from Labeled and Unlabeled Documents using EM

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The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon

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On the Asymptotic Improvement in the Out- come of Supervised Learning Provided by Additional Nonsupervised Learning

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Maximum Likelihood from Incomplete Data Via the EM Algorithm

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Combining labeled and unlabeled data with co-training

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Analyzing the effectiveness and applicability of co-training

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Making Large-Scale SVM Learning Practical

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Statistical Learning Theory

inferredcites →https://doi.org/10.5555/299094openalex-snapshot

Advances in kernel methods: support vector learning

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Democracy is good for ranking

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O efeito do uso de diferentes formas de extração de termos na compreensibilidade e representatividade dos termos em coleções textuais na língua portuguesa

inferred← citeshttps://doi.org/10.11606/t.55.2009.tde-05042010-162834openalex-snapshot

Contribuições para a construção de taxonomias de tópicos em domínios restritos utilizando aprendizado estatístico

inferred← citeshttps://doi.org/10.1186/1471-2105-13-75openalex-snapshot

Quantitatively integrating molecular structure and bioactivity profile evidence into drug-target relationship analysis

inferred← citeshttps://doi.org/10.1201/ebk1420072617-bopenalex-snapshot

References

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Information Processing and Management

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Data Quality Evaluation and Improvement for Machine Learning

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Hessian-Regularized Co-Training for Social Activity Recognition

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An Adaptive Moment estimation method for online AUC maximization

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Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning

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Efficient Reformulation of 1-Norm Ranking SVM

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Multi-View Correlated Feature Learning by Uncovering Shared Component

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Multi-View Clustering in Latent Embedding Space

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Active Learning with Multiple Views

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Semi-supervised structured prediction models

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Understanding and exploiting user intent in community question answering

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Improving Classification and Attribute Clustering: An Iterative Semi-supervised Approach

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Design and Analysis of Techniques for Multiple-Instance Learning in the Presence of Balanced and Skewed Class Distributions

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L1-penalized AUC-optimization with a surrogate loss

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Discriminative models for semi-supervised natural language learning

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Visual recognition by learning from web data

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Learning with multiple representations : algorithms and applications

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Discovering visual patterns for image data analysis

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RECENT ADVANCES ON SUPPORT VECTOR MACHINES RESEARCH

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Semi-Supervised Learning

inferred← citeshttps://doi.org/10.48550/arxiv.1304.5634openalex-snapshot

A Survey on Multi-view Learning

inferred← citeshttps://doi.org/10.48550/arxiv.1903.03386openalex-snapshot

Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia

inferred← citeshttps://doi.org/10.5220/0003791802400245openalex-snapshot

SEMI-SUPERVISED LEARNING OF ALTERNATIVELY SPLICED EXONS USING EXPECTATION MAXIMIZATION TYPE APPROACHES

inferred← citeshttps://doi.org/10.5555/1953048.2078190openalex-snapshot

Bayesian Co-Training

inferred← citeshttps://doi.org/10.70675/34212fe0z1031z46d4zb0e0z039e12fc4585openalex-snapshot

Learning a Multiview Weighted Majority Vote Classifier : Using PAC-Bayesian Theory and Boosting

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