A regularization framework for active learning from imbalanced data

A regularization framework for active learning from imbalanced data

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.

Bibliographic Details
Main Author:	Paskov, Hristo Spassimirov
Other Authors:	Tomaso A. Poggio and Lorenzo A. Rosasco.
Format:	Thesis
Language:	eng
Published:	Massachusetts Institute of Technology 2011
Subjects:	Electrical Engineering and Computer Science.
Online Access:	http://hdl.handle.net/1721.1/61177

Similar Items

Stable Machine Learning
by: Paskov, Ivan Spassimirov
Published: (2022)

Imbalanced data learning for biomedical application
by: Xie, Vincent JianHan.
Published: (2011)

Classification of imbalanced data
by: Tay, Hui Ling
Published: (2018)

Machine learning for balanced and imbalanced data
by: Ding, Shuya
Published: (2016)

A direct ensemble classifier for learning imbalanced multiclass data
by: Samry @ Mohd Shamrie Sainin
Published: (2013)

Box drawings for learning with imbalanced data
by: Goh, Siong Thye, et al.
Published: (2015)

The information regularization framework for semi-supervised learning
by: Corduneanu, Adrian (Adrian Dumitru), 1977-
Published: (2007)

Ensemble classifier and resampling for imbalanced multiclass learning
by: Sainin, Mohd Shamrie, et al.
Published: (2015)

Learning Performance Prediction with Imbalanced Virtual Learning Environment Students’ Interactions Data
by: Chen, Hsing-Chung, et al.
Published: (2022)

Fuzzy and smote resampling technique for imbalanced data sets
by: Zorkeflee, Maisarah, et al.
Published: (2015)

Multiple centers based fuzzy clustering for imbalanced data
by: Liao, Hongda
Published: (2016)

Fuzzy distance-based undersampling technique for imbalanced flood data
by: Ku-Mahamud, Ku Ruhana, et al.
Published: (2016)

A direct ensemble classifier for imbalanced multiclass learning
by: Sainin, Mohd Shamrie, et al.
Published: (2012)

DML-PL: deep metric learning based pseudo-labeling framework for class imbalanced semi-supervised learning
by: Yan, Mi, et al.
Published: (2023)

Distribution-sensitive learning for imbalanced datasets
by: Song, Yale, et al.
Published: (2014)

Challenging issues in classification problems : sparisty control, key instance detection, and imbalanced data
by: Liu, Guoqing.
Published: (2013)

A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
by: Mohd Razali, Muhamad Hasbullah, et al.
Published: (2021)

Evaluating integrated weight linear method to class imbalanced learning in video data
by: Mohd Apandi, Ziti Fariha, et al.
Published: (2011)

Towards imbalanced image classification : a generative adversarial network ensemble learning method
by: Huang, Yangru, et al.
Published: (2020)

Logistic regression methods for classification of imbalanced data sets
by: Santi Puteri Rahayu, -
Published: (2012)

Reinforcement learning for imbalanced vehicle booming noise classification
by: Yang, J, et al.
Published: (2023)

Data augmentation approach for language identification in imbalanced bilingual code-mixed social media datasets
by: Mohd Suhairi, Md Suhaimin, et al.
Published: (2023)

RSG: A simple but effective module for learning imbalanced datasets
by: Wang, J, et al.
Published: (2021)

Regularized algorithms for ranking, and manifold learning for related tasks
by: Zacharia, Giorgos, 1974-
Published: (2009)

Policy regularized model predictive control framework for robust legged locomotion
by: Bledt, Gerardo
Published: (2018)

Addressing imbalanced EEG data for improved microsleep detection: An ADASYN, FFT and LDA-based approach
by: Hasan, Md Mahmudul, et al.
Published: (2024)

Ensemble deep random vector functional link neural net for imbalanced datasets
by: Soo, Jian Xian
Published: (2022)

Radius-SMOTE: A New Oversampling Technique of Minority Samples Based on Radius Distance for Learning from Imbalanced Data
by: Pradipta, G.A., et al.
Published: (2021)

Validation assessments on resampling method in imbalanced binary classification for linear discriminant analysis
by: Jamaluddin, Ahmad Hakiim, et al.
Published: (2021)

Comparison of imbalanced data treatments: a case study on cleft lip and palate data
by: Zaturrawiah Ali Omar, et al.
Published: (2020)

Deep reinforcement learning for multi-class imbalanced training: applications in healthcare
by: Yang, J, et al.
Published: (2023)

Solving the Imbalanced and Limited Data Labeled for Automated Essay Scoring using Cost Sensitive XGBoost and Pseudo-Labeling
by: Pramularsih, Marvina, et al.
Published: (2022)

Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
by: Mahat, Nor Idayu, et al.

Lyapunov Analysis of Two Imbalanced Power System Areas
by: Pratama, Gilang Nugraha Putu, et al.

Regular and irregular signal resampling
by: Russell, Andrew Ian, 1975-
Published: (2006)

Self-paced regularization in label distribution learning
by: Koh, Terence Kang Wei
Published: (2019)

PyMedServer : a server framework for mobile data collection and machine learning
by: Mofor Nkaze, John.
Published: (2020)

Deep Imbalanced Regression: Challenges, Methods, and Applications
by: Zha, Kaiwen
Published: (2022)

Adjusted Geometric−mean: A Novel Performance Measure for Imbalanced Bioinformatics Datasets Learning
by: Batuwita, R, et al.
Published: (2012)

An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets
by: Ahmad, Azlin, et al.
Published: (2021)