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Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

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Showing 1701–1750 of 10307 papers

TitleStatusHype
Adverse Drug Reaction Detection in Twitter Using RoBERTa and Rules—0
A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis—0
A privacy-preserving data storage and service framework based on deep learning and blockchain for construction workers' wearable IoT sensors—0
Adversary ML Resilience in Autonomous Driving Through Human Centered Perception Mechanisms—0
Active Learning with Transfer Learning—0
A Prior Knowledge Based Tumor and Tumoral Subregion Segmentation Tool for Pediatric Brain Tumors—0
A Primer on Pretrained Multilingual Language Models—0
Adversary Helps: Gradient-based Device-Free Domain-Independent Gesture Recognition—0
A Pretrained DenseNet Encoder for Brain Tumor Segmentation—0
Adversarial Vulnerability of Active Transfer Learning—0
Active Learning of Ordinal Embeddings: A User Study on Football Data—0
Accelerating Matrix Diagonalization through Decision Transformers with Epsilon-Greedy Optimization—0
A Preliminary Study on Environmental Sound Classification Leveraging Large-Scale Pretrained Model and Semi-Supervised Learning—0
A predictive physics-aware hybrid reduced order model for reacting flows—0
Adversarial Transfer of Pose Estimation Regression—0
Adversarial Transfer Learning for Punctuation Restoration—0
A Practical Guide to Fine-tuning Language Models with Limited Data—0
Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates—0
Contextualized Attention-based Knowledge Transfer for Spoken Conversational Question Answering—0
A Practical Approach towards Causality Mining in Clinical Text using Active Transfer Learning—0
Approximation by non-symmetric networks for cross-domain learning—0
Active Learning for Rumor Identification on Social Media—0
Approximate Grassmannian Intersections: Subspace-Valued Subspace Learning—0
Approximated Prompt Tuning for Vision-Language Pre-trained Models—0
FlowBERT: Prompt-tuned BERT for variable flow field prediction—0
Contextualized Cross-Lingual Event Trigger Extraction with Minimal Resources—0
CG-CNN: Self-Supervised Feature Extraction Through Contextual Guidance and Transfer Learning—0
Continual Learning for Anomaly Detection in Surveillance Videos—0
Continual Lifelong Learning with Neural Networks: A Review—0
Adversarial Training Helps Transfer Learning via Better Representations—0
Approaching Neural Chinese Word Segmentation as a Low-Resource Machine Translation Task—0
Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis—0
Approaches for enhancing extrapolability in process-based and data-driven models in hydrology—0
Applying Transfer Learning To Deep Learned Models For EEG Analysis—0
Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning—0
Applying Transfer Learning for Improving Domain-Specific Search Experience Using Query to Question Similarity—0
Applying Knowledge Transfer for Water Body Segmentation in Peru—0
Adversarial Teacher-Student Learning for Unsupervised Domain Adaptation—0
Applying Deep Neural Networks to automate visual verification of manual bracket installations in aerospace—0
Applied Computer Vision on 2-Dimensional Lung X-Ray Images for Assisted Medical Diagnosis of Pneumonia—0
Active Learning Approaches to Enhancing Neural Machine Translation—0
Context-Aware Policy Reuse—0
Active flow control for three-dimensional cylinders through deep reinforcement learning—0
Adversarial-Robust Transfer Learning for Medical Imaging via Domain Assimilation—0
Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning—0
Application of Transfer Learning Approaches in Multimodal Wearable Human Activity Recognition—0
Application of Transfer Learning and Ensemble Learning in Image-level Classification for Breast Histopathology—0
Adversarial Robustness of Discriminative Self-Supervised Learning in Vision—0
Adversarial Network Compression—0
Application of Low-resource Machine Translation Techniques to Russian-Tatar Language Pair—0
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All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified