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 10151–10200 of 10307 papers

TitleStatusHype
Free speech or Free Hate Speech? Analyzing the Proliferation of Hate Speech in Parler—0
FreeTransfer-X: Safe and Label-Free Cross-Lingual Transfer from Off-the-Shelf Models—0
Freezing the Pivot for Triangular Machine Translation—0
FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning—0
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks—0
From augmented microscopy to the topological transformer: a new approach in cell image analysis for Alzheimer's research—0
From Fake to Hyperpartisan News Detection Using Domain Adaptation—0
From fat droplets to floating forests: cross-domain transfer learning using a PatchGAN-based segmentation model—0
From FreEM to D'AlemBERT: a Large Corpus and a Language Model for Early Modern French—0
From High-SNR Radar Signal to ECG: A Transfer Learning Model with Cardio-Focusing Algorithm for Scenarios with Limited Data—0
From Isolated Islands to Pangea: Unifying Semantic Space for Human Action Understanding—0
From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs—0
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks—0
From Limited Labels to Open Domains: An Efficient Learning Paradigm for UAV-view Geo-Localization—0
From Macro to Micro: Boosting micro-expression recognition via pre-training on macro-expression videos—0
From Multi-label Learning to Cross-Domain Transfer: A Model-Agnostic Approach—0
From N to N+1: Multiclass Transfer Incremental Learning—0
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models—0
Frustratingly Easy Natural Question Answering—0
Frustratingly Easy Transferability Estimation—0
FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task—0
FTL: A universal framework for training low-bit DNNs via Feature Transfer—0
Full or Weak annotations? An adaptive strategy for budget-constrained annotation campaigns—0
Fully Automated and Standardized Segmentation of Adipose Tissue Compartments by Deep Learning in Three-dimensional Whole-body MRI of Epidemiological Cohort Studies—0
Fully Automated Hand Hygiene Monitoring\ Operating Room using 3D Convolutional Neural Network—0
Fully Automatic Electrocardiogram Classification System based on Generative Adversarial Network with Auxiliary Classifier—0
Fully Convolutional Networks for Diabetic Foot Ulcer Segmentation—0
Fully Distributed Fog Load Balancing with Multi-Agent Reinforcement Learning—0
Fully probabilistic design for knowledge fusion between Bayesian filters under uniform disturbances—0
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch—0
Functional Annotation of Human Cognitive States using Graph Convolution Networks—0
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery—0
Function Encoders: A Principled Approach to Transfer Learning in Hilbert Spaces—0
Functions that Emerge through End-to-End Reinforcement Learning - The Direction for Artificial General Intelligence -—0
Fundamental Computational Limits in Pursuing Invariant Causal Prediction and Invariance-Guided Regularization—0
Fundamental Limits of Transfer Learning in Binary Classifications—0
FundaQ-8: A Clinically-Inspired Scoring Framework for Automated Fundus Image Quality Assessment—0
Fusarium Damaged Kernels Detection Using Transfer Learning on Deep Neural Network Architecture—0
Fused Deep Neural Network based Transfer Learning in Occluded Face Classification and Person re-Identification—0
G2L: A Geometric Approach for Generating Pseudo-labels that Improve Transfer Learning—0
G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks—0
Gain from Neighbors: Boosting Model Robustness in the Wild via Adversarial Perturbations Toward Neighboring Classes—0
Gait recognition via deep learning of the center-of-pressure trajectory—0
Galaxy Classification Using Transfer Learning and Ensemble of CNNs With Multiple Colour Spaces—0
GAMA++: Disentangled Geometric Alignment with Adaptive Contrastive Perturbation for Reliable Domain Transfer—0
Gameplay Highlights Generation—0
Gap Minimization for Knowledge Sharing and Transfer—0
GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning—0
Gastrointestinal Disorder Detection with a Transformer Based Approach—0
Gastrointestinal Mucosal Problems Classification with Deep Learning—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