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 5801–5850 of 10307 papers

TitleStatusHype
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities—0
Model Inversion Attack against Transfer Learning: Inverting a Model without Accessing It—0
Leveraging universality of jet taggers through transfer learning—0
BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs—0
GSDA: Generative Adversarial Network-based Semi-Supervised Data Augmentation for Ultrasound Image Classification—0
A Survey of Surface Defect Detection of Industrial Products Based on A Small Number of Labeled Data—0
A survey of underwater acoustic data classification methods using deep learning for shoreline surveillance—0
Reprogramming FairGANs with Variational Auto-Encoders: A New Transfer Learning Model—0
Transferring Dual Stochastic Graph Convolutional Network for Facial Micro-expression Recognition—0
Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems—0
Unsupervised Alignment of Distributional Word Embeddings—0
Rethinking Task Sampling for Few-shot Vision-Language Transfer LearningCode0
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting—0
Multi-Agent Policy Transfer via Task Relationship Modeling—0
Adaptive Trajectory Prediction via Transferable GNN—0
Towards Inadequately Pre-trained Models in Transfer Learning—0
Data augmentation with mixtures of max-entropy transformations for filling-level classification—0
HyperPELT: Unified Parameter-Efficient Language Model Tuning for Both Language and Vision-and-Language Tasks—0
Discriminability-Transferability Trade-Off: An Information-Theoretic PerspectiveCode0
HintNet: Hierarchical Knowledge Transfer Networks for Traffic Accident Forecasting on Heterogeneous Spatio-Temporal DataCode0
Learning from Few Examples: A Summary of Approaches to Few-Shot Learning—0
Generalization Through The Lens Of Leave-One-Out ErrorCode0
Knowledge Transfer in Deep Reinforcement Learning for Slice-Aware Mobility Robustness Optimization—0
Self-supervised learning for analysis of temporal and morphological drug effects in cancer cell imaging dataCode0
Exploration of Various Deep Learning Models for Increased Accuracy in Automatic Polyp Detection—0
Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy OptimizationCode0
On partitioning of an SHM problem and parallels with transfer learning—0
Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer NetworksCode0
Transfer Learning of High-Fidelity Opacity Spectra in Autoencoders and Surrogate Models—0
Visual Feature Encoding for GNNs on Road Networks—0
Self-supervised Transformer for Deepfake Detection—0
Hyperspectral Pixel Unmixing with Latent Dirichlet Variational Autoencoder—0
A Versatile Agent for Fast Learning from Human Instructors—0
Transfer Learning Algorithm with Knowledge Division LevelCode0
Improving Response Time of Home IoT Services in Federated LearningCode0
A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learning—0
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension TaskCode0
A Deep Learning Approach for Network-wide Dynamic Traffic Prediction during Hurricane Evacuation—0
Learn From the Past: Experience Ensemble Knowledge Distillation—0
A Survey of Multilingual Models for Automatic Speech Recognition—0
The Reality of Multi-Lingual Machine Translation—0
Oolong: Investigating What Makes Transfer Learning Hard with Controlled StudiesCode0
Collaborative Training of Heterogeneous Reinforcement Learning Agents in Environments with Sparse Rewards: What and When to Share?Code0
Towards Unsupervised Domain Adaptation via Domain-Transformer—0
Absolute Zero-Shot LearningCode0
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality—0
Multi-fidelity reinforcement learning framework for shape optimization—0
Domain-Augmented Domain Adaptation—0
Simplified Learning of CAD Features Leveraging a Deep Residual AutoencoderCode0
Probabilities of the Third Type: Statistical Relational Learning and Reasoning with Relative Frequencies—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