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An Optimization Framework for Combining Ensembles of Classifiers and Clusterers with Applications to Nontransductive Semisupervised Learning and Transfer Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data
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Advances in Soft Computing — AFSS 2002
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Some Notes on Alternating Optimization
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Introduction to Semi-Supervised Learning
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Learning Continuous Latent Variable Models with Bregman Divergences
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Semi-supervised Classification Based on Clustering Ensembles
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C 3E: A Framework for Combining Ensembles of Classifiers and Clusterers
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Knowledge Reuse Mechanisms for Categorizing Related Image Sets
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On-Line Algorithms in Machine Learning
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Guest editor’s introduction: special issue on inductive transfer learning
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Analysis of decision boundaries in linearly combined neural classifiers
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The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
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Collaborative clustering with background knowledge
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Classifier ensembles: Select real-world applications
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A simultaneous learning framework for clustering and classification
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Parallel optimization: Theory, algorithms, and applications
inferredcites →https://doi.org/10.1080/08839510802170546openalex-snapshot
CONSENSUS-BASED ENSEMBLES OF SOFT CLUSTERINGS
inferredcites →https://doi.org/10.1090/s0002-9939-1959-0105008-8openalex-snapshot
Proximity Maps for Convex Sets
inferredcites →https://doi.org/10.1109/36.934070openalex-snapshot
Best-bases feature extraction algorithms for classification of hyperspectral data
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Proceedings of 1994 IEEE International Symposium on Information Theory
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Learning latent variable models with bregman divergences
inferredcites →https://doi.org/10.1109/msp.2007.4286565openalex-snapshot
Bootstrap - Inspired Techniques in Computation Intelligence
inferredcites →https://doi.org/10.1109/tgrs.2006.878442openalex-snapshot
Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data
inferredcites →https://doi.org/10.1109/tkde.2011.206openalex-snapshot
A Graph-Based Consensus Maximization Approach for Combining Multiple Supervised and Unsupervised Models
inferredcites →https://doi.org/10.1137/1.9781611972740.22openalex-snapshot
Clustering with Bregman Divergences
inferredcites →https://doi.org/10.1137/1.9781611972825.95openalex-snapshot
An Iterative and Re-weighting Framework for Rejection and Uncertainty Resolution in Crowdsourcing
inferredcites →https://doi.org/10.1145/1015330.1015414openalex-snapshot
Solving cluster ensemble problems by bipartite graph partitioning
inferredcites →https://doi.org/10.1145/1102351.1102467openalex-snapshot
Propagating distributions on a hypergraph by dual information regularization
inferredcites →https://doi.org/10.1145/1148170.1148253openalex-snapshot
Large scale semi-supervised linear SVMs
inferredcites →https://doi.org/10.1145/1150402.1150510openalex-snapshot
Linear prediction models with graph regularization for web-page categorization
inferredcites →https://doi.org/10.1145/1273496.1273521openalex-snapshot
Boosting for transfer learning
inferredcites →https://doi.org/10.1145/1281192.1281218openalex-snapshot
Co-clustering based classification for out-of-domain documents
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
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Graph transduction via alternating minimization
inferredcites →https://doi.org/10.1145/1401890.1401928openalex-snapshot
Knowledge transfer via multiple model local structure mapping
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10.1162/153244303321897735
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Combining Pattern Classifiers: Methods and Algorithms
inferredcites →https://doi.org/10.1214/aos/1176346060openalex-snapshot
On the Convergence Properties of the EM Algorithm
inferredcites →https://doi.org/10.1561/9781601984616openalex-snapshot
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
inferredcites →https://doi.org/10.17877/de290r-14262openalex-snapshot
Making Large-Scale SVM Learning Practical
inferredcites →https://doi.org/10.2307/1909424openalex-snapshot
Nonlinear Programming: A Unified Approach
inferredcites →https://doi.org/10.5555/1046920.1194913openalex-snapshot
Convergence Theorems for Generalized Alternating Minimization Procedures
inferredcites →https://doi.org/10.5555/1248547.1248548openalex-snapshot
Statistical Comparisons of Classifiers over Multiple Data Sets
inferredcites →https://doi.org/10.5555/1953048.2078212openalex-snapshot
Semi-Supervised Learning with Measure Propagation
inferredcites →https://doi.org/10.5555/299094openalex-snapshot
Advances in kernel methods: support vector learning
inferredcites →https://doi.org/10.5555/777092.777110openalex-snapshot
Cluster ensembles: a knowledge reuse framework for combining partitionings
inferredcites →https://doi.org/10.5555/964885.964886openalex-snapshot
Convergence of alternating optimization
inferredcites →https://doi.org/10.7551/mitpress/6173.003.0003openalex-snapshot
Introduction to Semi-Supervised Learning
inferredcites →https://doi.org/10.7551/mitpress/6173.003.0016openalex-snapshot
Label Propagation and Quadratic Criterion
inferredcites →https://doi.org/10.7551/mitpress/9780262033589.001.0001openalex-snapshot
Semi-Supervised Learning
inferredcites →https://doi.org/10.7551/mitpress/9780262033589.003.0011openalex-snapshot
Label Propagation and Quadratic Criterion
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Core Decomposition of Massive, Information-Rich Graphs
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Regularization for Graph-Based Transfer Learning Text Classification
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On Cross-Domain Transfer in Venue Recommendation
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An Effective and Cost-Based Framework for a Qualitative Hybrid Data Deduplication
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Prick the filter bubble: A novel cross domain recommendation model with adaptive diversity regularization
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Accumulative categorization: Online 3D shape classification for progressive collections
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Using unsupervised information to improve semi-supervised tweet sentiment classification
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Combining clustering and active learning for the detection and learning of new image classes
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Study on the Influential Factors of Micro-blog Forwarding
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Ensemble Transfer Learning Algorithm
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Combining Classification and Clustering for Tweet Sentiment Analysis
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RPC: An Efficient Classifier Ensemble Using Random Projections
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A weighted-resampling based transfer learning algorithm
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Hybrid Classifier Ensemble for Imbalanced Data
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Cluster-level Emotion Pattern Matching for Cross-Domain Social Emotion Classification
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Cluster’s Quality Evaluation and Selective Clustering Ensemble
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TDAN: Transferable Domain Adversarial Network for Link Prediction in Heterogeneous Social Networks
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Abordagens para combinar classificadores e agrupadores em problemas de classificação
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Análise de sentimentos em textos curtos provenientes de redes sociais
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Using metaheuristics to optimize the combination of classifier and cluster ensembles
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Personalized Image Classification by Semantic Embedding and Active Learning
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