A Survey on Transfer Learning

2009/10/16 by Sinno Jialin Pan, Qiang Yang · 942 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #Machine Learning and Algorithms #Machine Learning and Data Classification

paper · doi:10.1109/tkde.2009.191

openalex publication_date 2009/10/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

Abstract

A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. However, in many real-world applications, this assumption may not hold. For example, we sometimes have a classification task in one domain of interest, but we only have sufficient training data in another domain of interest, where the latter data may be in a different feature space or follow a different data distribution. In such cases, knowledge transfer, if done successfully, would greatly improve the performance of learning by avoiding much expensive data-labeling efforts. In recent years, transfer learning has emerged as a new learning framework to address this problem. This survey focuses on categorizing and reviewing the current progress on transfer learning for classification, regression, and clustering problems. In this survey, we discuss the relationship between transfer learning and other related machine learning techniques such as domain adaptation, multitask learning and sample selection bias, as well as covariate shift. We also explore some potential future issues in transfer learning research.

Citations

• Domain Adaptation via Transfer Component Analysis

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• Semi-Supervised Domain Adaptation via Selective Pseudo Labeling and Progressive Self-Training
• CoMMiT: Co-informed inference of microbiome-metabolome interactions via transfer learning
• A survey of the recent architectures of deep convolutional neural networks
• A New Perspective On AI Safety Through Control Theory Methodologies
• Pruning by Block Benefit: Exploring the Properties of Vision Transformer Blocks during Domain Adaptation
• Learning beyond datasets: Knowledge Graph Augmented Neural Networks for Natural language Processing
• Recent Advances in Zero-shot Recognition
• Audio Spoofing Verification using Deep Convolutional Neural Networks by Transfer Learning
• Are Fast Methods Stable in Adversarially Robust Transfer Learning?
• Domain Adaption for Knowledge Tracing
• Seismic resolution enhancement via deep Learning with Knowledge Distillation and Domain Adaptation
• Multi-View Contrastive Learning for Robust Domain Adaptation in Medical Time Series Analysis
• Domain Adaptive Neural Networks for Object Recognition
• An Efficient Method for the Classification of Croplands in Scarce-Label Regions
• Transductive Zero-Shot Learning with a Self-training dictionary approach
• 3W Dataset 2.0.0: a realistic and public dataset with rare undesirable real events in oil wells
• Brain2Model Transfer: Training sensory and decision models with human neural activity as a teacher
• Smell Pittsburgh: Community-Empowered Mobile Smell Reporting System
• Transfer Learning using Representation Learning in Massive Open Online Courses
• Composite Neural Network: Theory and Application to PM2.5 Prediction
• Known-class Aware Self-ensemble for Open Set Domain Adaptation
• A Comprehensive Survey on Transfer Learning
• HMD Vision-based Teleoperating UGV and UAV for Hostile Environment using Deep Learning
• Deep Transfer Network: Unsupervised Domain Adaptation
• Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning
• Generalizing vision-language models to novel domains: A comprehensive survey
• A Computer Vision Approach to Combat Lyme Disease
• Sparsely-Labeled Source Assisted Domain Adaptation
• Automated Detection of Dolphin Whistles with Convolutional Networks and Transfer Learning
• LLM-Enhanced Multimodal Fusion for Cross-Domain Sequential Recommendation
• Detecting aquatic plant transmission on floatplanes using computer vision
• Time-Contrastive Pretraining for In-Context Image and Video Segmentation
• Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision
• Predictive case control designs for modification learning
• ML for Flood Forecasting at Scale
• AI-based Approach in Early Warning Systems: Focus on Emergency Communication Ecosystem and Citizen Participation in Nordic Countries
• Joint Geometrical and Statistical Alignment for Visual Domain Adaptation
• Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation
• Variational Learning of Disentangled Representations
• Learning from Multiple Corrupted Sources, with Application to Learning from Label Proportions
• Private Training & Data Generation by Clustering Embeddings
• Energy-Based Transfer for Reinforcement Learning
• Less Annotating, More Classifying: Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and BERT-NLI
• Deep Learning in Ultrasound Elastography Imaging
• Evaluating the structure of cognitive tasks with transfer learning
• 2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets
• A Survey on Curriculum Learning
• Easy Transfer Learning By Exploiting Intra-domain Structures
• T-SVDNet: Exploring High-Order Prototypical Correlations for Multi-Source Domain Adaptation
• Generative Knowledge Transfer for Neural Language Models
• A framework for enriching survey datasets using passive data and machine learning, with an application to transferring attitudinal variables across transport surveys
• Simplification of Training Data for Cross-Project Defect Prediction
• Deep Learning Surrogates for Real-Time Gas Emission Inversion
• Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
• Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet
• Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners
• Cross-lingual Dataless Classification for Languages with Small Wikipedia Presence
• Knowledge Projection for Deep Neural Networks
• Subdomain Adaptation with Manifolds Discrepancy Alignment
• Tackling Imbalanced Data in Cybersecurity with Transfer Learning: A Case with ROP Payload Detection
• Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets
• Real-time stored product insect detection and identification using deep learning: System integration and extensibility to mobile platforms
• Learning from Multiple Noisy Partial Labelers
• Iterative Machine Teaching
• QFFT, Question-Free Fine-Tuning for Adaptive Reasoning
• Research Frontiers in Transfer Learning -- a systematic and bibliometric review
• Environment Transfer for Distributed Systems
• Multi-Task Learning via Co-Attentive Sharing for Pedestrian Attribute Recognition
• Latent Representation Learning of Multi-scale Thermophysics: Application to Dynamics in Shocked Porous Energetic Material
• Praxis-BGM: Clustering of Omics Data Using Semi-Supervised Transfer Learning for Gaussian Mixture Models via Natural-Gradient Variational Inference
• Machine Learning Methods for Small Data and Upstream Bioprocessing Applications: A Comprehensive Review
• Poisoning the Unlabeled Dataset of Semi-Supervised Learning
• AutoGen Driven Multi Agent Framework for Iterative Crime Data Analysis and Prediction
• Adaptive Personalized Federated Learning
• Transfer Learning for Future Wireless Networks: A Comprehensive Survey
• Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation
• Text Detection on Roughly Placed Books by Leveraging a Learning-based Model Trained with Another Domain Data
• SIMSHIFT: A Benchmark for Adapting Neural Surrogates to Distribution Shifts
• Instance-Based Transfer Learning with Similarity-Aware Subject Selection for Cross-Subject SSVEP-Based BCIs
• Domain adaptation for person re-identification on new unlabeled data using AlignedReID++
• Cross-Lingual Adaptation using Structural Correspondence Learning
• Hierarchical Adaptive Structural SVM for Domain Adaptation
• Slimming Down LLMs Without Losing Their Minds
• Exploring Visual Prompting: Robustness Inheritance and Beyond
• On Inverse Problems, Parameter Estimation, and Domain Generalization
• Concept-Based Unsupervised Domain Adaptation
• Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation
• Explainable Deep Image Classifiers for Skin Lesion Diagnosis
• TALL -- A Trainable Architecture for Enhancing LLM Performance in Low-Resource Languages
• Generalized Online Transfer Learning for Climate Control in Residential\n Buildings
• Enhancing Efficiency and Propulsion in Bio-mimetic Robotic Fish through End-to-End Deep Reinforcement Learning
• Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction
• Transferable Positive/Negative Speech Emotion Recognition via Class-wise Adversarial Domain Adaptation
• Kernel Robust Bias-Aware Prediction under Covariate Shift
• Transfer learning for Remaining Useful Life Prediction Based on Consensus Self-Organizing Models
• A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks
• Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series
• Stable Prediction with Model Misspecification and Agnostic Distribution Shift
• LORM: Learning to Optimize for Resource Management in Wireless Networks with Few Training Samples
• Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding
• CryptoRec: Privacy-preserving Recommendation as a Service
• Structural Regularization
• Multi-Tasking Genetic Algorithm (MTGA) for Fuzzy System Optimization
• Style Normalization and Restitution for Domain Generalization and Adaptation
• Industrial Robot Trajectory Tracking Using Multi-Layer Neural Networks Trained by Iterative Learning Control
• Adversarial Consistent Learning on Partial Domain Adaptation of PlantCLEF 2020 Challenge
• Generalized Constraints as A New Mathematical Problem in Artificial Intelligence: A Review and Perspective
• Writer-Aware CNN for Parsimonious HMM-Based Offline Handwritten Chinese Text Recognition
• Interactive user interface based on Convolutional Auto-encoders for annotating CT-scans
• Attention-based Transfer Learning for Brain-computer Interface
• Learning to Interpret Satellite Images Using Wikipedia
• Deep Transfer Learning for Cross-domain Activity Recognition
• Iterative Dual Domain Adaptation for Neural Machine Translation
• Izhikevich-Inspired Temporal Dynamics for Enhancing Privacy, Efficiency, and Transferability in Spiking Neural Networks
• Support and Invertibility in Domain-Invariant Representations
• Multi-Party Dual Learning
• A Survey on Spatial and Spatiotemporal Prediction Methods
• Investigating the Impact of Data Volume and Domain Similarity on Transfer Learning Applications
• Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration
• Sim-to-Real Domain Adaptation For High Energy Physics
• Domain Agnostic Few-Shot Learning For Document Intelligence
• DAVE: Deriving Automatically Verilog from English
• Transfer Topic Modeling with Ease and Scalability
• Three-dimensional convolutional neural network (3D-CNN) for heterogeneous material homogenization
• DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks
• Generic Object Detection With Dense Neural Patterns and Regionlets
• Towards Robust Pattern Recognition: A Review
• GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability
• Disentangled State Space Representations
• Active Generative Adversarial Network for Image Classification
• Deep learning empowers genomic selection of pest-resistant grapevine
• PoisHygiene: Detecting and Mitigating Poisoning Attacks in Neural Networks
• Generalizing from a Few Examples: A Survey on Few-Shot Learning
• Target Semantics Clustering via Text Representations for Robust Universal Domain Adaptation
• Meta-learning with negative learning rates
• Constrained Deep Transfer Feature Learning and its Applications
• MHTN: Modal-adversarial Hybrid Transfer Network for Cross-modal Retrieval
• Asymptotically perfect seeded graph matching without edge correlation (and applications to inference)
• DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation
• Drowsiness Detection Based On Driver Temporal Behavior Using a New Developed Dataset
• Improving Unsupervised Domain Adaptation by Reducing Bi-level Feature Redundancy
• Billion-scale semi-supervised learning for image classification
• Flexible End-to-End Dialogue System for Knowledge Grounded Conversation
• Multi-Platform Methane Plume Detection via Model and Domain Adaptation
• Privacy Preserving Recalibration under Domain Shift
• ProteinBERT: a universal deep-learning model of protein sequence and function
• Metamorphic Testing for Object Detection Systems
• DDTCDR: Deep Dual Transfer Cross Domain Recommendation
• Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework
• Deep-Learning Convolutional Neural Networks for scattered shrub detection with Google Earth Imagery
• Domain adaptation under structural causal models
• Multi-Task Incremental Learning for Object Detection
• COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning
• Automatic detection of overshooting tops and their properties from visible satellite channels
• Efficient Endangered Deer Species Monitoring with UAV Aerial Imagery and Deep Learning
• StarCraft Micromanagement with Reinforcement Learning and Curriculum Transfer Learning
• Transfer Learning for Improving Singing-voice Detection in Polyphonic Instrumental Music
• Searching Neural Architectures for Sensor Nodes on IoT Gateways
• Homogeneous Online Transfer Learning with Online Distribution Discrepancy Minimization
• Adaptive Multi-Source Causal Inference
• Reuse and Adaptation for Entity Resolution through Transfer Learning
• Deep Learning Bandgaps of Topologically Doped Graphene
• Using Multi-task and Transfer Learning to Solve Working Memory Tasks
• Unsupervised Domain Adaptation Based on Source-guided Discrepancy
• No species left behind: borrowing strength to map data-deficient species
• Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer Learning
• Frequency-Adaptive Discrete Cosine-ViT-ResNet Architecture for Sparse-Data Vision
• A Comprehensive Survey on Test-Time Adaptation Under Distribution Shifts
• Transductive Zero-Shot Action Recognition by Word-Vector Embedding
• Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials
• Limited Generalizability in Argument Mining: State-Of-The-Art Models Learn Datasets, Not Arguments
• Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks
• Stable Learning via Sample Reweighting
• A Multi-output Gaussian Process Regression with Negative Transfer Mitigation for Generating Boundary Test Scenarios of Multi-UAV Systems
• When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey
• Continual Learning on the Edge with TensorFlow Lite
• Caching Policy for Cache-enabled D2D Communications by Learning User Preference
• COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19
• The EIHW-GLAM Deep Attentive Multi-model Fusion System for Cough-based COVID-19 Recognition in the DiCOVA 2021 Challenge
• A Novel BiLevel Paradigm for Image-to-Image Translation
• Vocabulary-informed Extreme Value Learning
• An Automated Deep Learning Approach for Bacterial Image Classification
• A Coalition-Based Communication Framework for Task-Driven Flying Ad-Hoc Networks
• Private Federated Learning with Domain Adaptation
• Learning to Ask Screening Questions for Job Postings
• Towards Corruption-Agnostic Robust Domain Adaptation
• Empirical Analysis of Image Caption Generation using Deep Learning
• Check-N-Run: A Checkpointing System for Training Deep Learning Recommendation Models
• PyTorchPipe: a framework for rapid prototyping of pipelines combining\n language and vision
• Convergence Analysis of Homotopy-SGD for non-convex optimization
• Task-Oriented Low-Label Semantic Communication With Self-Supervised Learning
• Predicting Onflow Parameters Using Transfer Learning for Domain and Task Adaptation
• Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines
• Continuous Domain Adaptation with Variational Domain-Agnostic Feature Replay
• Unsupervised Domain Adaptation on Reading Comprehension
• Network Signatures from Image Representation of Adjacency Matrices: Deep/Transfer Learning for Subgraph Classification
• Transfer Learning for Thermal Comfort Prediction in Multiple Cities
• Transfer learning of regression models from a sequence of datasets by penalized estimation
• Causality and Generalizability: Identifiability and Learning Methods
• Domain Adaptation Using Adversarial Learning for Autonomous Navigation
• Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation
• Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules
• Refining Language Models with Compositional Explanations
• Learning the Pareto Frontier of Predictive Models under Distribution Shift
• Learning with Feature Evolvable Streams
• On monitoring development indicators using high resolution satellite images
• Wasserstein Transfer Learning
• Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
• Recognizing License Plates in Real-Time
• Decoupling Representation and Learning in Genetic Programming: the LaSER Approach
• Improved Deep Learning of Object Category using Pose Information
• CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning
• Multi-Channel Transfer Learning of Chest X-ray Images for Screening of COVID-19
• Content Selection in Data-to-Text Systems: A Survey
• A systematic review of machine learning approaches to bovine tuberculosis in cattle
• Privacy for Rescue: A New Testimony Why Privacy is Vulnerable In Deep Models
• HeNet: A Deep Learning Approach on Intel^\circledR Processor Trace for Effective Exploit Detection
• Domain Adaptive Medical Image Segmentation via Adversarial Learning of Disease-Specific Spatial Patterns
• Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning
• DEAAN: Disentangled Embedding and Adversarial Adaptation Network for Robust Speaker Representation Learning
• Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning
• Transferrable Operative Difficulty Assessment in Robot-assisted Teleoperation: A Domain Adaptation Approach
• Representation as a Service
• Traffic Modelling and Prediction via Symbolic Regression on Road Sensor Data
• Online Transfer Learning: Negative Transfer and Effect of Prior Knowledge
• Unified AI for Accurate Audio Anomaly Detection
• Integration of TinyML and LargeML: A Survey of 6G and Beyond
• LOD1 3D City Model from LiDAR: The Impact of Segmentation Accuracy on Quality of Urban 3D Modeling and Morphology Extraction
• Generalized Category Discovery via Token Manifold Capacity Learning
• Fusing Cross-Domain Knowledge from Multimodal Data to Solve Problems in the Physical World
• Transfer-Learning-Based Approach to Retrieve the Cloud Properties Using Diverse Remote Sensing Datasets
• Physics-Driven Machine Learning Algorithm Facilitates Multilayer Cloud Property Retrievals From Geostationary Passive Imager Measurements
• Dual-Domain Fusion Convolutional Neural Network for Contrast Enhancement Forensics
• Tasks Structure Regularization in Multi-Task Learning for Improving Facial Attribute Prediction
• Estimating multi-class dynamic origin-destination demand through a forward-backward algorithm on computational graphs
• Transfer Learning for Mixed-Integer Resource Allocation Problems in Wireless Networks
• A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards
• Hard Class Rectification for Domain Adaptation
• Agile Domain Adaptation
• Transfer Learning by Asymmetric Image Weighting for Segmentation across Scanners
• Knowledge Transfer with Jacobian Matching
• Improve SGD Training via Aligning Mini-batches
• Self-adaptive Re-weighted Adversarial Domain Adaptation
• Mamba-Adaptor: State Space Model Adaptor for Visual Recognition
• AI for marketing: Enabler? Engager? Ersatz?
• OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning
• Expanding phenological insights: automated phenostage annotation with community science plant images
• Conditional Bures Metric for Domain Adaptation
• Multi-task Dictionary Learning based Convolutional Neural Network for Computer aided Diagnosis with Longitudinal Images
• Task Affinity with Maximum Bipartite Matching in Few-Shot Learning
• Weight Distillation: Transferring the Knowledge in Neural Network Parameters
• Deep learning-based synthetic-CT generation in radiotherapy and PET: a review
• Visual Transfer Learning: Informal Introduction and Literature Overview
• ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale
• Regularization for Deep Learning: A Taxonomy
• GOUHFI: a novel contrast- and resolution-agnostic segmentation tool for Ultra-High Field MRI
• ReadOnce Transformers: Reusable Representations of Text for Transformers
• ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models
• Deep learning models are not robust against noise in clinical text
• Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles
• Convolutional Neural Networks for Histopathology Image Classification: Training vs. Using Pre-Trained Networks
• Leveraging Real-Time Data Analysis and Multiple Kernel Learning for Manufacturing of Innovative Steels
• Augmented Inverse Hybrid Weighting: Robust Inference under Deterministic and Random Distribution Shifts
• A Foliated View of Transfer Learning
• A Survey on Deep Neural Network Pruning: Taxonomy, Comparison, Analysis, and Recommendations
• Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions
• DeepSeqCoco: A Robust Mobile Friendly Deep Learning Model for Detection of Diseases in Cocos nucifera
• Improving speech recognition models with small samples for air traffic control systems
• Multi-Stage Transfer Learning with an Application to Selection Process
• XL-NBT: A Cross-lingual Neural Belief Tracking Framework
• Parameter Reference Loss for Unsupervised Domain Adaptation
• Predicting butterfly species presence from satellite imagery using soft contrastive regularisation
• Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review
• Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency
• Eye-2-I: Eye-tracking for just-in-time implicit user profiling
• Learning Invariant Representations across Domains and Tasks
• A Large-scale Benchmark on Geological Fault Delineation Models: Domain Shift, Training Dynamics, Generalizability, Evaluation and Inferential Behavior
• Transfer Learning for Material Classification using Convolutional Networks
• Scalable bundling via dense product embeddings
• Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder
• Cross-Database Micro-Expression Recognition: A Benchmark
• Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems
• Is Discriminator a Good Feature Extractor?
• Barley Variety Identification by iPhone Images and Deep Learning
• Transfer Learning Across Fixed-Income Product Classes
• ActiLabel: A Combinatorial Transfer Learning Framework for Activity Recognition
• Learning ULMFiT and Self-Distillation with Calibration for Medical Dialogue System
• Graph Neural Networks Exponentially Lose Expressive Power for Node Classification
• Applications of machine learning to machine fault diagnosis: A review and roadmap
• Towards Cross-Project Defect Prediction with Imbalanced Feature Sets
• Multiple-Source Adaptation for Regression Problems
• Supervised Opinion Aspect Extraction by Exploiting Past Extraction Results
• Accumulating Knowledge for Lifelong Online Learning
• Emerging ML-AI Techniques for Analog and RF EDA
• Federated Adversarial Domain Adaptation
• Enhancing Inference for Small Cohorts via Transfer Learning and Weighted Integration of Multiple Datasets
• SmartPilot: A Multiagent CoPilot for Adaptive and Intelligent Manufacturing
• Transfer Learning Toolkit: Primers and Benchmarks
• Semi-Supervised Active Learning for Support Vector Machines: A Novel Approach that Exploits Structure Information in Data
• NSF-MAP: Neurosymbolic Multimodal Fusion for Robust and Interpretable Anomaly Prediction in Assembly Pipelines
• Cross-domain Semantic Parsing via Paraphrasing
• Towards a continuous modeling of natural language domains
• A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes
• Unsupervised Transfer Learning with Self-Supervised Remedy
• Automated Knot Detection and Pairing for Wood Analysis in the Timber Industry
• A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithms
• Active and Adaptive Sequential learning
• A Mixture of Expert Approach for Low-Cost Customization of Deep Neural Networks
• Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
• Real-time Federated Evolutionary Neural Architecture Search
• Express Your Doubts -- Probabilistic World Modeling Should not be Based on Token logprobs
• A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges
• AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation
• REPAINT: Knowledge Transfer in Deep Reinforcement Learning
• Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions
• HiLLIE: Human-in-the-Loop Training for Low-Light Image Enhancement
• Cross-Domain MLP and CNN Transfer Learning for Biological Signal Processing: EEG and EMG
• DA-HOC
• Discriminately Decreasing Discriminability with Learned Image Filters
• A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO 2 Sensor Data
• Soft-Masked Semi-Dual Optimal Transport for Partial Domain Adaptation
• MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records
• Discriminative Label Consistent Domain Adaptation
• What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Data
• An Optimization Framework for Semi-Supervised and Transfer Learning using Multiple Classifiers and Clusterers
• Deep Reinforcement Learning: An Overview
• Sparse Spectrum Gaussian Process for Bayesian Optimization
• AdaFilter: Adaptive Filter Fine-tuning for Deep Transfer Learning
• Deep learning in bioinformatics: introduction, application, and perspective in big data era
• KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
• Fine-Tuning Without Forgetting: Adaptation of YOLOv8 Preserves COCO Performance
• Convex Discriminative Multitask Clustering
• Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation
• The Future of Misinformation Detection: New Perspectives and Trends
• Machine Translation of Low-Resource Indo-European Languages
• Quantitative Parametric Mapping of Tissues Properties from Standard Magnetic Resonance Imaging Enabled by Deep Learning
• Measuring Information Transfer in Neural Networks
• Self-Paced Contextual Reinforcement Learning
• Machine Learning with World Knowledge: The Position and Survey
• Human-In-The-Loop Person Re-Identification
• Combining satellite imagery and machine learning to predict poverty
• DESK: A Robotic Activity Dataset for Dexterous Surgical Skills Transfer to Medical Robots
• Knowledge-Driven Machine Learning: Concept, Model and Case Study on Channel Estimation
• Fractional Transfer Learning for Deep Model-Based Reinforcement Learning
• Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation
• Unsupervised Cross-Domain Recognition by Identifying Compact Joint Subspaces
• An Empirical Framework for Domain Generalization in Clinical Settings
• Beyond Sharing Weights for Deep Domain Adaptation
• Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection
• Deep learning to infer eddy heat fluxes from sea surface height patterns of mesoscale turbulence
• Demystifying Parallel and Distributed Deep Learning
• A Survey on Data Collection for Machine Learning: a Big Data -- AI Integration Perspective
• Veni Vidi Vici, A Three-Phase Scenario For Parameter Space Analysis in Image Analysis and Visualization
• MADAN: Multi-source Adversarial Domain Aggregation Network for Domain Adaptation
• Pain Intensity Estimation by a Self--Taught Selection of Histograms of Topographical Features
• Curriculum Learning of Multiple Tasks
• Surf at MEDIQA 2019: Improving Performance of Natural Language Inference in the Clinical Domain by Adopting Pre-trained Language Model
• Explainable AI for Engineering Design: A Unified Approach of Systems Engineering and Component- Based Deep Learning Demonstrated by Energy- Efficient Building Design
• Automated Monitoring Cropland Using Remote Sensing Data: Challenges and Opportunities for Machine Learning
• Robust Ensembling Network for Unsupervised Domain Adaptation
• Feature Alignment and Restoration for Domain Generalization and Adaptation
• Mining Social Media for Newsgathering: A Review
• Progressive Data Science: Potential and Challenges
• Multi-stage domain adversarial style reconstruction for cytopathological image stain normalization
• Sequential Transfer in Multi-armed Bandit with Finite Set of Models
• Spatial Variability Aware Deep Neural Networks (SVANN): A General Approach
• Transfer Learning for Speech and Language Processing
• Multi-Modal Music Information Retrieval: Augmenting Audio-Analysis with Visual Computing for Improved Music Video Analysis
• Generative adversarial networks in time series: A survey and taxonomy
• Non-Structured DNN Weight Pruning -- Is It Beneficial in Any Platform?
• Frustratingly Easy Transferability Estimation
• Target Consistency for Domain Adaptation: when Robustness meets Transferability
• A punishment voting algorithm based on super categories construction for acoustic scene classification
• Filtering with State-Observation Examples via Kernel Monte Carlo Filter
• A Time-Series Data Augmentation Model through Diffusion and Transformer Integration
• Transfer Learning with Sparse Associative Memories
• Subject Information Extraction for Novelty Detection with Domain Shifts
• Multi-level datasets training method in Physics-Informed Neural Networks
• Kernel Density Machines
• CNN based common approach to handwritten character recognition of multiple scripts
• Argumentation Mining
• Multi-Stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting
• Yet Another Text Captcha Solver
• A Brief Review for Compression and Transfer Learning Techniques in DeepFake Detection
• Deep neural network recognition of shallow water corals in the Gulf of Eilat (Aqaba)
• Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving
• AI Supply Chains: An Emerging Ecosystem of AI Actors, Products, and Services
• Machine Learning-Based Modeling of the Anode Heel Effect in X-ray Beam Monte Carlo Simulations
• SoCodeCNN: Program Source Code for Visual CNN Classification Using Computer Vision Methodology
• QTIP: Quick simulation-based adaptation of traffic model per incident parameters
• Transferring Autonomous Driving Knowledge on Simulated and Real\n Intersections
• Transfer Learning for Loan Recovery Prediction under Distribution Shifts with Heterogeneous Feature Spaces
• Deep learning for time series classification
• Breast cancer diagnosis: A systematic review
• AI Developments for T and B Cell Receptor Modeling and Therapeutic Design
• Extrapolating Expected Accuracies for Large Multi-Class Problems
• Neuron Coverage-Guided Domain Generalization
• Unsupervised Adaptive Semantic Segmentation with Local Lipschitz Constraint
• A learning approach to enhance assurances for real-time self-adaptive systems
• Applications of Machine Learning in Document Digitisation
• Towards Stable and Comprehensive Domain Alignment: Max-Margin Domain-Adversarial Training
• Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling
• Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning
• Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning
• Transfer Learning Based Automatic Model Creation Tool For Resource Constraint Devices
• Learning to Interpret Satellite Images in Global Scale Using Wikipedia
• A Novel Taxonomy and Classification Scheme for Code Smell Interactions
• Fault Detection in New Wind Turbines with Limited Data by Generative Transfer Learning
• Test Time Adaptation Methods for Point Cloud Registration in Laparoscopic Surgery
• Challenges in Benchmarking Stream Learning Algorithms with Real-world Data
• CANet: ChronoAdaptive Network for Enhanced Long-Term Time Series Forecasting under Non-Stationarity
• Disaster Monitoring using Unmanned Aerial Vehicles and Deep Learning
• Predicting Water Temperature Dynamics of Unmonitored Lakes With Meta‐Transfer Learning
• A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems
• SRoll3: A neural network approach to reduce large-scale systematic effects in the Planck High-Frequency Instrument maps
• Transductive Zero-Shot Hashing for Multilabel Image Retrieval
• Deep Learning segmentation with metal intrusion for quantitative microstructure analysis of hardened cement paste
• Indigenization of urban mobility
• End-to-end Models with auditory attention in Multi-channel Keyword Spotting
• Transfer Learning-Based Dynamic Multiobjective Optimization Algorithms
• Elastic Coupled Co-clustering for Single-Cell Genomic Data
• Inducing a hierarchy for multi-class classification problems
• Probabilistic Inference for Structural Health Monitoring: New Modes of Learning from Data
• Active deep learning method for the discovery of objects of interest in large spectroscopic surveys
• A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns
• Artificial intelligence in cancer pathology: Applications, challenges, and future directions
• Distributionally Robust Transfer Learning with Structurally Missing Covariates, with Application to Cross-National Cardiac Arrest Prediction
• GradMix: Multi-source Transfer across Domains and Tasks
• Multi-task, multi-label and multi-domain learning with residual convolutional networks for emotion recognition
• Smart buildings as Cyber-Physical Systems: Data-driven predictive control strategies for energy efficiency
• Kernel Manifold Alignment for Domain Adaptation
• Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning
• Learned Indexes for Dynamic Workloads
• PEMNET: A Transfer Learning-based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems
• Modeling Users’ Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection
• Fine Tuning a Simulation-Driven Estimator
• Heterogeneous Domain Adaptation via Soft Transfer Network
• Modality Compensation Network: Cross-Modal Adaptation for Action Recognition
• Two Sides of the Same Coin
• A new transfer learning framework with application to model-agnostic multi-task learning
• Unsupervised transfer learning for anomaly detection: Application to complementary operating condition transfer
• Using convolutional neural networks to predict galaxy metallicity from three-colour images
• Efficient Adaptation of Deep Neural Networks for Semantic Segmentation in Space Applications
• Sparse Array Selection Across Arbitrary Sensor Geometries With Deep Transfer Learning
• On the impact of selected modern deep-learning techniques to the performance and celerity of classification models in an experimental high-energy physics use case
• Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual Learning
• Learning from Few Samples: A Survey
• The Iterative Chainlet Partitioning Algorithm for the Traveling Salesman Problem with Drone and Neural Acceleration
• Cognitive-Inspired Hierarchical Attention Fusion With Visual and Textual for Cross-Domain Sequential Recommendation
• Combining predictions from linear models when training and test inputs\n differ
• Deep Learning with Pretrained 'Internal World' Layers: A Gemma 3-Based Modular Architecture for Wildfire Prediction
• Breast density classification with deep convolutional neural networks
• Inverse design optimization framework via a two-step deep learning approach: application to a wind turbine airfoil
• Interventional Domain Adaptation
• Domain Adaptation with Optimal Transport on the Manifold of SPD matrices
• Minimum Class Confusion for Versatile Domain Adaptation
• Neuro-evolutionary Frameworks for Generalized Learning Agents
• A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability
• SelfHAR
• A survey on incorporating domain knowledge into deep learning for medical image analysis
• Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
• Deep transfer network with joint distribution adaptation: A new intelligent fault diagnosis framework for industry application
• Robust unsupervised domain adaptation for neural networks via moment alignment
• Deep learning for biomedical photoacoustic imaging: A review
• Transfer Regression via Pairwise Similarity Regularization
• Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night
• MetaDSE: A Few-shot Meta-learning Framework for Cross-workload CPU Design Space Exploration
• Optical Transient Object Classification in Wide-field Small Aperture Telescopes with a Neural Network
• Automatic model based dataset generation for fast and accurate crop and weeds detection
• Cluster-based zero-shot learning for multivariate data
• Action Segmentation with Mixed Temporal Domain Adaptation
• A Survey on Open Set Recognition
• DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs
• Seeing permeability from images: fast prediction with convolutional neural networks
• Supervised Metric Learning with Generalization Guarantees
• Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
• Analysis of Diffractive Optical Neural Networks and Their Integration With Electronic Neural Networks
• Hierarchical ResNeXt Models for Breast Cancer Histology Image Classification
• Continual Learning in Practice
• Multi-Scale Gradual Integration CNN for False Positive Reduction in Pulmonary Nodule Detection
• Predicting Quantum Many-Body Dynamics with Transferable Neural Networks*
• Fast rates by transferring from auxiliary hypotheses
• Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise
• A mean-field optimal control formulation of deep learning
• Deep learning for sensor-based activity recognition: A survey
• Learning to Selectively Transfer
• Deep model with Siamese network for viable and necrotic tumor regions assessment in osteosarcoma
• Unsupervised Audio-Visual Subspace Alignment for High-Stakes Deception Detection
• Neural Network for Nanoscience Scanning Electron Microscope Image Recognition
• A Data-centric Supervised Transfer Learning Framework for DOA Estimation with Array Imperfections
• A Discriminative Technique for Multiple-Source Adaptation
• Learning to Match Distributions for Domain Adaptation
• Transfer Learning via Auxiliary Labels with Application to Cold-Hardiness Prediction
• A critique of pure learning and what artificial neural networks can learn from animal brains
• Comparative Evaluation of Radiomics and Deep Learning Models for Disease Detection in Chest Radiography
• Performance Analysis of Deep Learning Models for Femur Segmentation in MRI Scan
• Poem Meter Classification of Recited Arabic Poetry: Integrating High-Resource Systems for a Low-Resource Task
• Transferable Deployment of Semantic Edge Inference Systems via Unsupervised Domain Adaption
• Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions
• Incremental Real-Time Personalization in Human Activity Recognition Using Domain Adaptive Batch Normalization
• Foundation Models for Environmental Science: A Survey of Emerging Frontiers
• Liver segmentation in abdominal CT images via auto-context neural network and self-supervised contour attention
• NeuroAdaptTrainer: A Fiji/ImageJ Plugin for YOLO-Based Neuron Segmentation, InteractiveCorrection and Transfer Learning
• Transfer learning for vision-based tactile sensing
• Deep Learning Approaches for Medical Imaging Under Varying Degrees of Label Availability: A Comprehensive Survey
• Matrix effects in laser-induced breakdown spectroscopy: A review from fundamental mechanisms to data-driven modeling strategies
• Inferring genotype-phenotype maps using attention models
• The Impact of Model Zoo Size and Composition on Weight Space Learning
• Beyond the Generative Learning Trilemma: Generative Model Assessment in Data Scarcity Domains
• Ensemble-Enhanced Graph Autoencoder with GAT and Transformer-Based Encoders for Robust Fault Diagnosis
• A Survey of Machine Learning Models and Datasets for the Multi-label Classification of Textual Hate Speech in English
• Autoencoder node saliency: Selecting relevant latent representations
• Domain Generalization via Semi-supervised Meta Learning
• PTRL: Prior Transfer Deep Reinforcement Learning for Legged Robots Locomotion
• Sparse Optimization for Transfer Learning: A L0-Regularized Framework for Multi-Source Domain Adaptation
• iTV: Inferring Traffic Violation-Prone Locations With Vehicle Trajectories and Road Environment Data

Related

• A Concise Review of Transfer Learning
• A Comprehensive Survey on Transfer Learning
• A Comprehensive Survey on Transfer Learning
• An introduction to domain adaptation and transfer learning
• A survey on domain adaptation theory: learning bounds and theoretical guarantees