Semi-Supervised Learning

No abstract is available for this paper.

• Publication year

  2014

• Venue

  Academic Press Library in Signal Processing

• Publication date

  Unknown publication date

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1016/B978-0-12-396502-8.00022-X
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Manifold regularization and semi-supervised learning: some theoretical analyses

  2013cited by this paper
• Semi-supervised Learning by Higher Order Regularization

  2011cited by this paper
• Lean Algebraic Multigrid (LAMG): Fast Graph Laplacian Linear Solver

  2011cited by this paper
• SystemML: Declarative machine learning on MapReduce

  2011cited by this paper
• Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning

  2011cited by this paper
• Behavior of Graph Laplacians on Manifolds with Boundary

  2011cited by this paper
• Multiscale Wavelets on Trees, Graphs and High Dimensional Data: Theory and Applications to Semi Supervised Learning

  2010cited by this paper
• A discriminative model for semi-supervised learning

  2010cited by this paper
• Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models

  2010cited by this paper
• Learning from Labeled and Unlabeled Data

  2010cited by this paper
• Empirical stationary correlations for semi-supervised learning on graphs

  2010cited by this paper
• Introduction to Semi-Supervised Learning

  2009cited by this paper
• Semi-Supervised Learning in Gigantic Image Collections

  2009cited by this paper
• Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification

  2009cited by this paper
• Maximum Entropy Discrimination Markov Networks

  2009cited by this paper
• Learning structural SVMs with latent variables

  2009cited by this paper
• Multilevel algorithms for linear ordering problems

  2009cited by this paper
• Wavelets on Graphs via Spectral Graph Theory

  2009cited by this paper
• Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data

  2009cited by this paper
• Multi-View Learning in the Presence of View Disagreement

  2008cited by this paper
• Large-scale manifold learning

  2008cited by this paper
• An RKHS for multi-view learning and manifold co-regularization

  2008cited by this paper
• Optimization Techniques for Semi-Supervised Support Vector Machines

  2008cited by this paper
• Semi-supervised structured prediction models

  2008cited by this paper
• Large scale manifold transduction

  2008cited by this paper
• Online Manifold Regularization: A New Learning Setting and Empirical Study

  2008cited by this paper
• Predicting Structured Data

  2007cited by this paper
• Multi-view Regression Via Canonical Correlation Analysis

  2007cited by this paper
• Local polynomial regression on unknown manifolds

  2007cited by this paper
• A tutorial on spectral clustering

  2007cited by this paper
• Statistical Analysis of Semi-Supervised Regression

  2007cited by this paper
• Book Reviews: Semisupervised Learning for Computational Linguistics by Steven Abney

  2007cited by this paper
• Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling

  2006cited by this paper
• Large Scale Transductive SVMs

  2006cited by this paper
• Branch and Bound for Semi-Supervised Support Vector Machines

  2006cited by this paper
• Graph Laplacians and their Convergence on Random Neighborhood Graphs

  2006cited by this paper
• Semi-supervised learning for structured output variables

  2006cited by this paper
• Structured Prediction, Dual Extragradient and Bregman Projections

  2006cited by this paper
• Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples

  2006cited by this paper
• Large scale semi-supervised linear SVMs

  2006cited by this paper
• Semi-Supervised Learning

  2006cited by this paper
• --1 CONTENTS

  2006cited by this paper
• Large Margin Methods for Structured and Interdependent Output Variables

  2005cited by this paper
• A PAC-Style Model for Learning from Labeled and Unlabeled Data

  2005cited by this paper
• Semi-Supervised Classification by Low Density Separation

  2005cited by this paper
• A Co-Regularization Approach to Semi-supervised Learning with Multiple Views

  2005cited by this paper
• Semi-supervised learning with sparse grids

  2005cited by this paper
• Maximum Margin Semi-Supervised Learning for Structured Variables

  2005cited by this paper
• Kernel conditional random fields: representation and clique selection

  2004cited by this paper
• Semi-Supervised Learning on Riemannian Manifolds

  2004cited by this paper
• Regularization and Semi-supervised Learning on Large Graphs

  2004cited by this paper
• Reproducing kernel Hilbert spaces in probability and statistics

  2004cited by this paper
• Max-Margin Markov Networks

  2003cited by this paper
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

  2003cited by this paper
• Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering

  2003cited by this paper
• Learning with Local and Global Consistency

  2003cited by this paper
• Kernels and Regularization on Graphs

  2003cited by this paper
• Measure Based Regularization

  2003cited by this paper
• A Distribution-Free Theory of Nonparametric Regression

  2002cited by this paper
• Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope

  2001cited by this paper
• A Random Walks View of Spectral Segmentation

  2001cited by this paper
• Partially labeled classification with Markov random walks

  2001cited by this paper
• Learning from Labeled and Unlabeled Data using Graph Mincuts

  2001cited by this paper
• Text Classification from Labeled and Unlabeled Documents using EM

  2000cited by this paper
• Learning Segmentation by Random Walks

  2000cited by this paper
• Transductive Inference for Text Classification using Support Vector Machines

  1999cited by this paper
• Unsupervised Models for Named Entity Classification

  1999cited by this paper
• Object recognition from local scale-invariant features

  1999cited by this paper
• Combining labeled and unlabeled data with co-training

  1998cited by this paper
• Statistical learning theory

  1998cited by this paper
• A gentle tutorial on the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models

  1997cited by this paper
• Introductory Functional Analysis: With Applications to Boundary Value Problems and Finite Elements

  1997cited by this paper
• Spectral Graph Theory

  1996cited by this paper
• The relative value of labeled and unlabeled samples in pattern recognition with an unknown mixing parameter

  1996cited by this paper
• Learning from a mixture of labeled and unlabeled examples with parametric side information

  1995cited by this paper
• On the exponential value of labeled samples

  1995cited by this paper
• Unsupervised Word Sense Disambiguation Rivaling Supervised Methods

  1995cited by this paper
• Spline Models for Observational Data

  1990cited by this paper
• Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper

  1977cited by this paper
• Journal of Machine Learning Research X (200x) X-x Generalization Error Bounds in Semi-supervised Classification under the Cluster Assumption

  year unknowncited by this paper

• Ensemble Methods

  2025cites this paper
• A Survey of Cross-Layer Security for Resource-Constrained IoT Devices

  2025cites this paper
• Semi-Supervised Piano Transcription Using Pseudo-Labeling Techniques

  2024cites this paper
• A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks

  2024cites this paper
• A Survey of Machine Learning in Edge Computing: Techniques, Frameworks, Applications, Issues, and Research Directions

  2024cites this paper
• MindDiffuser: Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusion

  2023cites this paper
• S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions

  2023influential citation
• Random forest feature selection for partial label learning

  2023cites this paper
• In all likelihoods: robust selection of pseudo-labeled data

  2023cites this paper
• Ten deep learning techniques to address small data problems with remote sensing

  2023cites this paper
• Pruning the Unlabeled Data to Improve Semi-Supervised Learning

  2023cites this paper
• Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption

  2023cites this paper
• Adinkra Symbol Recognition using Classical Machine Learning and Deep Learning

  2023cites this paper
• On the Benefits of Semi-Supervised Test Case Generation for Cyber-Physical Systems

  2023cites this paper
• A systematic review for class-imbalance in semi-supervised learning

  2023cites this paper
• Positive-Unlabeled Node Classification with Structure-aware Graph Learning

  2023cites this paper
• Semi-Supervised Learning via Swapped Prediction for Communication Signal Recognition

  2023cites this paper
• Not Just Learning From Others but Relying on Yourself: A New Perspective on Few-Shot Segmentation in Remote Sensing

  2023cites this paper
• A Unified Framework for Connecting Noise Modeling to Boost Noise Detection

  2023cites this paper
• Semi-Supervised Sound Event Detection with Local and Global Consistency Regularization

  2023cites this paper
• Improving Automatic Target Recognition in Low Data Regime using Semi-Supervised Learning and Generative Data Augmentation

  2023cites this paper
• WebUI: A Dataset for Enhancing Visual UI Understanding with Web Semantics

  2023influential citation
• Distributed denial of service attack prediction: Challenges, open issues and opportunities

  2023cites this paper
• On the Benefits of Semi-Supervised Test Case Generation for Simulation Models

  2023cites this paper
• Artificial intelligence for natural product drug discovery

  2023cites this paper
• Semi-supervised Learning with Support Isolation by Small-Paced Self-Training

  2023cites this paper
• Best Practices in Active Learning for Semantic Segmentation

  2023cites this paper
• Social relation-driven consensus reaching in large-scale group decision-making using semi-supervised classification

  2023cites this paper
• Pelvic floor MRI segmentation based on semi-supervised deep learning

  2023cites this paper
• Multi-Method Self-Training: Improving Code Generation With Text, And Vice Versa

  2023cites this paper
• Active pairwise distance learning for efficient labeling of large datasets by human experts

  2023cites this paper
• FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning

  2023cites this paper
• ProtWave-VAE: Integrating autoregressive sampling with latent-based inference for data-driven protein design

  2023cites this paper
• Evolutionary Dynamic Optimization and Machine Learning

  2023cites this paper
• Deep Neural Network-Based Automatic Dicentric Chromosome Detection Using a Model Pretrained on Common Objects

  2023cites this paper
• Semi-Supervised Learning in the Few-Shot Zero-Shot Scenario

  2023cites this paper
• DualMatch: Robust Semi-supervised Learning with Dual-Level Interaction

  2023cites this paper
• Investigating permafrost carbon dynamics in Alaska with artificial intelligence

  2023cites this paper
• A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning

  2023cites this paper
• Training Image Derivatives: Increased Accuracy and Universal Robustness

  2023cites this paper
• Semi-supervised ViT knowledge distillation network with style transfer normalization for colorectal liver metastases survival prediction

  2023cites this paper
• How to Do Machine Learning with Small Data? - A Review from an Industrial Perspective

  2023cites this paper
• Robust Semi-Supervised Learning when Not All Classes have Labels

  2022cites this paper
• On robust risk-based active-learning algorithms for enhanced decision support

  2022cites this paper
• AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images

  2022cites this paper
• Boosting Semi-Supervised Learning with Contrastive Complementary Labeling

  2022cites this paper
• A Method for Discovering Novel Classes in Tabular Data

  2022influential citation
• Pair-Based Joint Encoding with Relational Graph Convolutional Networks for Emotion-Cause Pair Extraction

  2022cites this paper
• The Benefits of Model-Based Generalization in Reinforcement Learning

  2022cites this paper
• Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model

  2022cites this paper
• Squeezing Data from a Rock: Machine Learning for Martian Science

  2022cites this paper
• Self-Paced Co-Training of Graph Neural Networks for Semi-Supervised Node Classification

  2022cites this paper
• Semi-Supervised Temporal Action Detection with Proposal-Free Masking

  2022cites this paper
• Semi-supervised learning with dropouts

  2022cites this paper
• Adaptive Semi-Supervised Inference for Optimal Treatment Decisions with Electronic Medical Record Data

  2022cites this paper
• Sparse Representation-Based Discriminative Metric Learning for Brain MRI Image Retrieval

  2022cites this paper
• Image Matting With Deep Gaussian Process

  2022cites this paper
• Integrating Semi-Supervised Learning with an Expert System for Vegetation Cover Classification Using Sentinel-2 and RapidEye Data

  2022cites this paper
• LAMDA-SSL: a comprehensive semi-supervised learning toolkit

  2022cites this paper
• Jointly optimized ensemble deep random vector functional link network for semi-supervised classification

  2022cites this paper
• AggMatch: Aggregating Pseudo Labels for Semi-Supervised Learning

  2022cites this paper
• Parameter-free Online Test-time Adaptation

  2022cites this paper
• From Statistical to Causal Learning

  2022cites this paper
• DetMatch: Two Teachers are Better Than One for Joint 2D and 3D Semi-Supervised Object Detection

  2022cites this paper
• Granular conditional entropy-based attribute reduction for partially labeled data with proxy labels

  2021cites this paper
• Unobserved classes and extra variables in high-dimensional discriminant analysis

  2021cites this paper
• A Survey on Deep Semi-Supervised Learning

  2021influential citation
• In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning

  2021cites this paper
• SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning

  2021cites this paper
• Nonparametric semi-supervised classification with application to signal detection in high energy physics

  2021cites this paper
• GraphHop: An Enhanced Label Propagation Method for Node Classification

  2021cites this paper
• Shelf Auditing Based on Image Classification Using Semi-Supervised Deep Learning to Increase On-Shelf Availability in Grocery Stores

  2021cites this paper
• Active Fire Detection in Landsat-8 Imagery: a Large-Scale Dataset and a Deep-Learning Study

  2021cites this paper
• Simulation-to-real domain adaptation with teacher–student learning for endoscopic instrument segmentation

  2021cites this paper
• Inductive Semi-supervised Learning Through Optimal Transport

  2021cites this paper
• LSDDL: Layer-Wise Sparsification for Distributed Deep Learning

  2021cites this paper
• A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision

  2021cites this paper
• Density-Based Distance Preserving Graph: Theoretical and Practical Analyses

  2021influential citation
• Semi-supervised learning for medical image classification using imbalanced training data

  2021cites this paper
• A Survey on Data-Driven Predictive Maintenance for the Railway Industry

  2021cites this paper
• Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey

  2021cites this paper
• A Bayesian Precision Medicine Framework for Calibrating Individualized Therapeutic Indices in Cancer

  2021cites this paper
• Transductive Few-Shot Learning: Clustering is All You Need?

  2021cites this paper
• A Survey on Semi-supervised Learning for Delayed Partially Labelled Data Streams

  2021cites this paper
• TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation

  2021cites this paper
• LCC-Net: A Lightweight Cross-Consistency Network for Semisupervised Cardiac MR Image Segmentation

  2021cites this paper
• Data-Driven Fault Diagnosis for Electric Drives: A Review

  2021cites this paper
• Building a training dataset for classification under a cost limitation

  2021cites this paper
• Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples

  2021cites this paper
• CLASSIFICATION BASED ON SEMI-SUPERVISED LEARNING: A REVIEW

  2021cites this paper
• Semi-Supervised Classification and Segmentation on High Resolution Aerial Images

  2021cites this paper
• The Shape of Learning Curves: A Review

  2021cites this paper
• Deep Learning based Cell Classification in Imaging Flow Cytometer

  2021cites this paper
• Mapping conditional distributions for domain adaptation under generalized target shift

  2021influential citation
• Graph-based semi-supervised one class support vector machine for detecting abnormal lung sounds

  2020cites this paper
• ESAD: End-to-end Semi-supervised Anomaly Detection

  2020cites this paper
• Out-distribution aware Self-training in an Open World Setting

  2020cites this paper
• Convergence Analysis of Homotopy-SGD for non-convex optimization

  2020cites this paper
• Ranking Neural Checkpoints

  2020cites this paper
• Pattern Classification Approaches for Breast Cancer Identification via MRI: State-Of-The-Art and Vision for the Future

  2020cites this paper