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 4351–4400 of 10307 papers

TitleStatusHype
Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers—0
Collective Knowledge Graph Completion with Mutual Knowledge Distillation—0
Transfer Learning for Personality Perception via Speech Emotion Recognition—0
Representation Transfer Learning via Multiple Pre-trained models for Linear Regression—0
READ: Recurrent Adaptation of Large Transformers—0
Deep Learning-based Bio-Medical Image Segmentation using UNet Architecture and Transfer Learning—0
Few-shot Unified Question Answering: Tuning Models or Prompts?—0
Selective Pre-training for Private Fine-tuningCode0
A Two-Step Deep Learning Method for 3DCT-2DUS Kidney Registration During Breathing—0
Beyond Shared Vocabulary: Increasing Representational Word Similarities across Languages for Multilingual Machine TranslationCode0
Deep Transductive Transfer Learning for Automatic Target Recognition—0
Topic-driven Distant Supervision Framework for Macro-level Discourse Parsing—0
Amplitude-Independent Machine Learning for PPG through Visibility Graphs and Transfer Learning—0
Cross-lingual Knowledge Transfer and Iterative Pseudo-labeling for Low-Resource Speech Recognition with Transducers—0
Feasibility of Transfer Learning: A Mathematical Framework—0
Sequential Transfer Learning to Decode Heard and Imagined Timbre from fMRI Data—0
LEAN: Light and Efficient Audio Classification Network—0
Regularization Through Simultaneous Learning: A Case Study on Plant Classification—0
A Comprehensive Survey of Sentence Representations: From the BERT Epoch to the ChatGPT Era and Beyond—0
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning ArchitectureCode0
An Optimized Ensemble Deep Learning Model For Brain Tumor Classification—0
Strategy Extraction in Single-Agent Games—0
Stock and market index prediction using Informer network—0
Crosslingual Transfer Learning for Low-Resource Languages Based on Multilingual Colexification GraphsCode0
Cross-lingual Transfer Can Worsen Bias in Sentiment Analysis—0
Explaining Emergent In-Context Learning as Kernel Regression—0
Transferring Fairness using Multi-Task Learning with Limited Demographic Information—0
CNN-based Methods for Object Recognition with High-Resolution Tactile SensorsCode0
Many or Few Samples? Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification—0
Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer in Prompt Tuning—0
Self-Distillation with Meta Learning for Knowledge Graph CompletionCode0
Evolutionary Algorithms in the Light of SGD: Limit Equivalence, Minima Flatness, and Transfer Learning—0
Self-supervised representations in speech-based depression detection—0
Model-based adaptation for sample efficient transfer in reinforcement learning control of parameter-varying systems—0
DADIN: Domain Adversarial Deep Interest Network for Cross Domain Recommender Systems—0
Exploring the Viability of Synthetic Query Generation for Relevance Prediction—0
Viewing Knowledge Transfer in Multilingual Machine Translation Through a Representational Lens—0
Interpretable neural architecture search and transfer learning for understanding CRISPR/Cas9 off-target enzymatic reactionsCode0
NollySenti: Leveraging Transfer Learning and Machine Translation for Nigerian Movie Sentiment ClassificationCode0
Pre-training Tensor-Train Networks Facilitates Machine Learning with Variational Quantum Circuits—0
Benchmarking Deep Learning Frameworks for Automated Diagnosis of Ocular Toxoplasmosis: A Comprehensive Approach to Classification and Segmentation—0
Comparison of Transfer Learning based Additive Manufacturing Models via A Case Study—0
Transfer Learning for Fine-grained Classification Using Semi-supervised Learning and Visual Transformers—0
Instruction Tuned Models are Quick LearnersCode0
G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks—0
Transfer Learning for Causal Effect Estimation—0
Privacy-Preserving Ensemble Infused Enhanced Deep Neural Network Framework for Edge Cloud Convergence—0
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech TranslationCode0
CB-HVTNet: A channel-boosted hybrid vision transformer network for lymphocyte assessment in histopathological images—0
Deep Reinforcement Learning to Maximize Arterial Usage during Extreme Congestion—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