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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4651–4700 of 10307 papers

TitleStatusHype
Offline Handwriting Signature Verification: A Transfer Learning and Feature Selection Approach—0
Offline-to-online hyperparameter transfer for stochastic bandits—0
oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions—0
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation—0
OmniDialog: An Omnipotent Pre-training Model for Task-Oriented Dialogue System—0
Omnidirectional Information Gathering for Knowledge Transfer-based Audio-Visual Navigation—0
OmniPD: One-Step Person Detection in Top-View Omnidirectional Indoor Scenes—0
Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning—0
On Adversarial Robustness of Language Models in Transfer Learning—0
On-chip Few-shot Learning with Surrogate Gradient Descent on a Neuromorphic Processor—0
On Conditional and Compositional Language Model Differentiable Prompting—0
On consequences of finetuning on data with highly discriminative features—0
On-Device Transfer Learning for Personalising Psychological Stress Modelling using a Convolutional Neural Network—0
One4all User Representation for Recommender Systems in E-commerce—0
On-edge Multi-task Transfer Learning: Model and Practice with Data-driven Task Allocation—0
On effects of Knowledge Distillation on Transfer Learning—0
One for Many: Transfer Learning for Building HVAC Control—0
One Model to Rule them All: Towards Zero-Shot Learning for Databases—0
One-Shot Transfer Learning for Nonlinear ODEs—0
One-stage Modality Distillation for Incomplete Multimodal Learning—0
One Step Is Enough for Few-Shot Cross-Lingual Transfer: Co-Training with Gradient Optimization—0
One System to Rule them All: a Universal Intent Recognition System for Customer Service Chatbots—0
One-To-Many Multilingual End-to-end Speech Translation—0
One-to-Many Semantic Communication Systems: Design, Implementation, Performance Evaluation—0
On evaluating CNN representations for low resource medical image classification—0
On Explaining Knowledge Distillation: Measuring and Visualising the Knowledge Transfer Process—0
On Generality and Knowledge Transferability in Cross-Domain Duplicate Question Detection for Heterogeneous Community Question Answering—0
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion—0
On Improving the Performance of Glitch Classification for Gravitational Wave Detection by using Generative Adversarial Networks—0
On Initializing Transformers with Pre-trained Embeddings—0
On Knowledge Distillation for Direct Speech Translation—0
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources—0
Online-Adaptive Anomaly Detection for Defect Identification in Aircraft Assembly—0
Online Bagging for Anytime Transfer Learning—0
Online Electric Vehicle Charging Detection Based on Memory-based Transformer using Smart Meter Data—0
Online Few-shot Gesture Learning on a Neuromorphic Processor—0
Online Gesture Recognition using Transformer and Natural Language Processing—0
Online Learning for Recommendations at Grubhub—0
Online Learning with Radial Basis Function Networks—0
Online Multi-Source Domain Adaptation through Gaussian Mixtures and Dataset Dictionary Learning—0
Online Policy Distillation with Decision-Attention—0
Online Sensor Hallucination via Knowledge Distillation for Multimodal Image Classification—0
Online Transfer Learning for RSV Case Detection—0
Online Transfer Learning in Reinforcement Learning Domains—0
Online Transfer Learning: Negative Transfer and Effect of Prior Knowledge—0
Online Video Super-Resolution with Convolutional Kernel Bypass Graft—0
On mechanisms for transfer using landmark value functions in multi-task lifelong reinforcement learning—0
On Neural Consolidation for Transfer in Reinforcement Learning—0
On partitioning of an SHM problem and parallels with transfer learning—0
On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning—0
Show:102550
← PrevPage 94 of 207Next →
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