SOTAVerified

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 6401–6425 of 10307 papers

TitleStatusHype
Cross-lingual Intermediate Fine-tuning improves Dialogue State TrackingCode0
How Different Text-preprocessing Techniques Using The BERT Model Affect The Gender Profiling of Authors—0
Knowledge Transfer based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis—0
Transfer learning with fewer ImageNet classes—0
Rumour Detection via Zero-shot Cross-lingual Transfer Learning—0
Expressive Power of Randomized Signature—0
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research—0
QBox: Partial Transfer Learning with Active Querying for Object DetectionCode0
Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning—0
DeepStroke: An Efficient Stroke Screening Framework for Emergency Rooms with Multimodal Adversarial Deep Learning—0
A Multi-stage Transfer Learning Framework for Diabetic Retinopathy Grading on Small Data—0
Simple and Effective Zero-shot Cross-lingual Phoneme RecognitionCode0
Energy efficient distributed analytics at the edge of the network for IoT environments—0
Transferring Knowledge from Vision to Language: How to Achieve it and how to Measure it?—0
Robust Generalization of Quadratic Neural Networks via Function Identification—0
Fully probabilistic design for knowledge fusion between Bayesian filters under uniform disturbances—0
SCSS-Net: Solar Corona Structures Segmentation by Deep LearningCode0
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents—0
Model Bias in NLP -- Application to Hate Speech Classification using transfer learning techniques—0
Background-Foreground Segmentation for Interior Sensing in Automotive Industry—0
Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization—0
Navigating the Kaleidoscope of COVID-19 Misinformation Using Deep Learning—0
A Study of the Generalizability of Self-Supervised Representations—0
Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision—0
Augmenting semantic lexicons using word embeddings and transfer learningCode0
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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