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 4151–4200 of 10307 papers

TitleStatusHype
Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation—0
Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement—0
Amplitude-Independent Machine Learning for PPG through Visibility Graphs and Transfer Learning—0
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks—0
Adaptive Trajectory Prediction via Transferable GNN—0
Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies—0
Data-efficient Modeling of Optical Matrix Multipliers Using Transfer Learning—0
Gradient Sparsification For Masked Fine-Tuning of Transformers—0
Data-Efficient Methods for Dialogue Systems—0
Data Efficient Lithography Modeling with Transfer Learning and Active Data Selection—0
Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices—0
Data-Efficient Information Extraction from Form-Like Documents—0
A comparative study of zero-shot inference with large language models and supervised modeling in breast cancer pathology classification—0
Data-Efficient Hate Speech Detection via Cross-Lingual Nearest Neighbor Retrieval with Limited Labeled Data—0
Data-Efficient Goal-Oriented Conversation with Dialogue Knowledge Transfer Networks—0
Automated Audio Captioning using Transfer Learning and Reconstruction Latent Space Similarity Regularization—0
Data Efficient Direct Speech-to-Text Translation with Modality Agnostic Meta-Learning—0
Adaptive Target Localization under Uncertainty using Multi-Agent Deep Reinforcement Learning with Knowledge Transfer—0
Adapting Amidst Degradation: Cross Domain Li-ion Battery Health Estimation via Physics-Guided Test-Time Training—0
Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning—0
Gradient Sparsification For Masked Fine-Tuning of Transformers—0
Data-Efficient Challenges in Visual Inductive Priors: A Retrospective—0
3D U-Net for segmentation of COVID-19 associated pulmonary infiltrates using transfer learning: State-of-the-art results on affordable hardware—0
Data-Driven Transferred Energy Management Strategy for Hybrid Electric Vehicles via Deep Reinforcement Learning—0
Data-Driven Transfer Learning Framework for Estimating Turning Movement Counts—0
AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction—0
Data-driven tool wear prediction in milling, based on a process-integrated single-sensor approach—0
Data-driven super-parameterization using deep learning: Experimentation with multi-scale Lorenz 96 systems and transfer-learning—0
Amortized Network Intervention to Steer the Excitatory Point Processes—0
Adaptive Sparse Transformer for Multilingual Translation—0
Autoencoding Features for Aviation Machine Learning Problems—0
Data-Driven Outage Restoration Time Prediction via Transfer Learning with Cluster Ensembles—0
Adaptive ship-radiated noise recognition with learnable fine-grained wavelet transform—0
Data-Driven Knowledge Transfer in Batch Q^* Learning—0
Data-driven inventory management for new products: An adjusted Dyna-Q approach with transfer learning—0
Autoencoder Based Sample Selection for Self-Taught Learning—0
Google is all you need: Semi-Supervised Transfer Learning Strategy For Light Multimodal Multi-Task Classification Model—0
Data-driven geophysics: from dictionary learning to deep learning—0
Data-Driven Deep Learning Based Hybrid Beamforming for Aerial Massive MIMO-OFDM Systems with Implicit CSI—0
Autocorrect for Estonian texts: final report from project EKTB25—0
Data-driven Approaches to Surrogate Machine Learning Model Development—0
Auto-Compressing Networks—0
Adaptive Sample Aggregation In Transfer Learning—0
A Comparative Study of Western and Chinese Classical Music based on Soundscape Models—0
GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling—0
GradMix: Multi-source Transfer across Domains and Tasks—0
Graph Enabled Cross-Domain Knowledge Transfer—0
Data-Centric AI in the Age of Large Language Models—0
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference—0
MSPM: A Modularized and Scalable Multi-Agent Reinforcement Learning-based System for Financial Portfolio Management—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