Active Learning through Adaptive Heterogeneous Ensembling

No abstract is available for this paper.

• Publication year

  2015

• Venue

  IEEE Transactions on Knowledge and Data Engineering

• Publication date

  2015-02-01

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/TKDE.2014.2304474
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Data Mining Practical Machine Learning Tools and Techniques

  2014influential reference
• Ensemble Pruning via Constrained Eigen-Optimization

  2012cited by this paper
• Multiobjective Neural Network Ensembles Based on Regularized Negative Correlation Learning

  2010cited by this paper
• Asking Generalized Queries to Domain Experts to Improve Learning

  2010cited by this paper
• Active Learning with Adaptive Heterogeneous Ensembles

  2009cited by this paper
• Active Learning Literature Survey

  2009cited by this paper
• Batch Mode Active Learning with Applications to Text Categorization and Image Retrieval

  2009cited by this paper
• An Analysis of Active Learning Strategies for Sequence Labeling Tasks

  2008cited by this paper
• Classifier Ensembles with a Random Linear Oracle

  2007cited by this paper
• Getting the Most Out of Ensemble Selection

  2006cited by this paper
• Reducing Labeling Effort for Structured Prediction Tasks

  2005cited by this paper
• Combining active and semi-supervised learning for spoken language understanding

  2005cited by this paper
• Is Combining Classifiers with Stacking Better than Selecting the Best One?

  2004cited by this paper
• Diverse ensembles for active learning

  2004cited by this paper
• Active learning using pre-clustering

  2004cited by this paper
• Constructing Diverse Classifier Ensembles using Artificial Training Examples

  2003cited by this paper
• Multiple Classifier Systems

  2000cited by this paper
• Support Vector Machine Active Learning with Applications to Text Classification

  2000cited by this paper
• Selective Sampling for Nearest Neighbor Classifiers

  1999cited by this paper
• The Random Subspace Method for Constructing Decision Forests

  1998influential reference
• Employing Em in Pool-based Active Learning for Text Classiication

  1998cited by this paper
• Employing EM and Pool-Based Active Learning for Text Classification

  1998cited by this paper
• Query Learning Strategies Using Boosting and Bagging

  1998influential reference
• A decision-theoretic generalization of on-line learning and an application to boosting

  1997cited by this paper
• Active Learning with Statistical Models

  1996cited by this paper
• Bagging Predictors

  1996cited by this paper
• Committee-Based Sampling For Training Probabilistic Classi(cid:12)ers

  1995cited by this paper
• Improving Generalization with Active Learning

  1994cited by this paper
• Heterogeneous Uncertainty Sampling for Supervised Learning

  1994cited by this paper
• A sequential algorithm for training text classifiers

  1994cited by this paper
• Query by committee

  1992cited by this paper
• Training Connectionist Networks with Queries and Selective Sampling

  1989cited by this paper
• Queries and concept learning

  1988cited by this paper

• Veri Madenciliğinde Karar Ağaçları İndükleyicilerinin Likert Ölçekli Verilerde Sınıflandırma Performansı

  2025cites this paper
• A Novel Denoising Method for Mud Continuous-Wave Signals Based on Selective Ensemble Strategy with Particle Swarm Optimization

  2025cites this paper
• Performance of Data Mining Algorithms for Classification of Likert Scale Data

  2025cites this paper
• Mastering Precision in Pivotal Variables Defining Wine Quality via Incremental Analysis of Baseline Accuracy

  2024cites this paper
• Decision Tree using Feature Grouping

  2023cites this paper
• SHSE: A subspace hybrid sampling ensemble method for software defect number prediction

  2022cites this paper
• Local variational Probabilistic Minimax Active Learning

  2022cites this paper
• Building heterogeneous ensembles by pooling homogeneous ensembles

  2021cites this paper
• On the Use of Deep Active Semi-Supervised Learning for Fast Rendering in Global Illumination

  2020cites this paper
• EER-ASSL: Combining Rollback Learning and Deep Learning for Rapid Adaptive Object Detection

  2020cites this paper
• Gaussian Process Regression Ensemble Model for Network Traffic Prediction

  2020cites this paper
• Functional gradient approach to probabilistic minimax active learning

  2019cites this paper
• Building heterogeneous ensembles by pooling homogeneous ones

  2019cites this paper
• Influence of environmental factors on human-like decision-making for intelligent ship

  2019cites this paper
• AEM: Attentional Ensemble Model for personalized classifier weight learning

  2019cites this paper
• AMANDA: DENSITY-BASED ADAPTIVE MODEL FOR NON-STATIONARY DATA UNDER EXTREME VERIFICATION LATENCY SCENARIOS

  2018cites this paper
• Pooling homogeneous ensembles to build heterogeneous ensembles

  2018cites this paper
• Very Fast C4.5 Decision Tree Algorithm

  2018cites this paper
• ISIS at Its Apogee: The Arabic Discourse on Twitter and What We Can Learn From That About ISIS Support and Foreign Fighters

  2018cites this paper
• Incremental Deep Learning for Robust Object Detection in Unknown Cluttered Environments

  2018influential citation
• A Divide-and-Conquer-Based Ensemble Classifier Learning by Means of Many-Objective Optimization

  2018cites this paper
• Recent advances in scaling‐down sampling methods in machine learning

  2017cites this paper
• Active and semi-supervised learning for object detection with imperfect data

  2017cites this paper
• Regex-based entity extraction with active learning and genetic programming

  2016cites this paper
• Ensemble based approach to increase vulnerability assessment and penetration testing accuracy

  2016influential citation
• Active learning approaches for learning regular expressions with genetic programming

  2016cites this paper
• An ensemble of deep learning architectures for automatic feature extraction

  2016cites this paper
• Discussion and review on evolving data streams and concept drift adapting

  2016cites this paper
• iSA: A fast, scalable and accurate algorithm for sentiment analysis of social media content

  2016cites this paper
• Multi-Instance Heterogeneous Classifiers with Extended Space forest

  2015cites this paper
• Recognizing Extended Spatiotemporal Expressions by Actively Trained Average Perceptron Ensembles

  2015influential citation
• Licensed under Creative Commons Attribution Cc by Advanced Methodologies Employed in Ensemble of Classifiers: a Survey

  year unknowncites this paper