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 3626–3650 of 10307 papers

TitleStatusHype
Color Enhancement for V-PCC Compressed Point Cloud via 2D Attribute Map Optimization—0
A Robust Deep Networks based Multi-Object MultiCamera Tracking System for City Scale Traffic—0
A Framework for Hierarchical Multilingual Machine Translation—0
Actor Critic with Differentially Private Critic—0
Attention on flow control: transformer-based reinforcement learning for lift regulation in highly disturbed flows—0
Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population—0
Colorectal cancer diagnosis from histology images: A comparative study—0
Collusion Detection with Graph Neural Networks—0
Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation—0
Collective Knowledge Graph Completion with Mutual Knowledge Distillation—0
Argument Novelty and Validity Assessment via Multitask and Transfer Learning—0
Collaborative Teacher-Student Learning via Multiple Knowledge Transfer—0
A Framework for Fast Scalable BNN Inference using Googlenet and Transfer Learning—0
Activity Recognition and Prediction in Real Homes—0
Collaborative Recommendation with Auxiliary Data: A Transfer Learning View—0
Collaborative Pressure Ulcer Prevention: An Automated Skin Damage and Pressure Ulcer Assessment Tool for Nursing Professionals, Patients, Family Members and Carers—0
Are You Really Okay? A Transfer Learning-based Approach for Identification of Underlying Mental Illnesses—0
Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control—0
Learning with Shared Representations: Statistical Rates and Efficient Algorithms—0
Are You Really Okay? A Transfer Learning-based Approach for Identification of Underlying Mental Illnesses—0
A foundational neural operator that continuously learns without forgetting—0
Collaborative Knowledge Fusion: A Novel Approach for Multi-task Recommender Systems via LLMs—0
Collaborative Group Learning—0
Are We Truly Forgetting? A Critical Re-examination of Machine Unlearning Evaluation Protocols—0
Collaborative Adversarial Learning for RelationalLearning on Multiple Bipartite Graphs—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