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Active Learning

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보존된 평가 기록: 7

Active Learning is a paradigm in supervised machine learning which uses fewer training examples to achieve better optimization by iteratively training a predictor, and using the predictor in each iteration to choose the training examples which will increase its chances of finding better configurations and at the same time improving the accuracy of the prediction model

Source: Polystore++: Accelerated Polystore System for Heterogeneous Workloads

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/adgaudio/O-MedAL

공식 코드

O-MedAL: Online Active Deep Learning for Medical Image Analysis

https://github.com/adityasaini70/unravel

공식 코드

Select Wisely and Explain: Active Learning and Probabilistic Local Post-hoc Explainability

https://github.com/ahachang/mitigate

공식 코드

Multitask Active Learning for Graph Anomaly Detection

https://github.com/ahalterman/ngec

공식 코드

Creating Custom Event Data Without Dictionaries: A Bag-of-Tricks

https://github.com/aim-lab/LUNet

공식 코드

LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus Images

https://github.com/aim-uofa/DiverGen

공식 코드

Generative Active Learning for Long-tailed Instance Segmentation

https://github.com/aimat-lab/PAL

공식 코드

PAL -- Parallel active learning for machine-learned potentials

https://github.com/aimat-lab/coarse-graining-al

공식 코드

Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations

https://github.com/aimotive/Compute-Efficient-Active-Learning

공식 코드

Compute-Efficient Active Learning

https://github.com/airi-institute/al_ats

공식 코드

Active Learning for Abstractive Text Summarization

https://github.com/airi-institute/al_nlp_feasible

공식 코드

Towards Computationally Feasible Deep Active Learning

https://github.com/ajedgley/rebound

공식 코드

ReBound: An Open-Source 3D Bounding Box Annotation Tool for Active Learning

https://github.com/akash2907/semi-sup-active-learning

공식 코드

Semi-supervised Active Learning for Video Action Detection

https://github.com/akoksal/meal

공식 코드

MEAL: Stable and Active Learning for Few-Shot Prompting

https://github.com/akshitjindal1/aot_wacv

공식 코드

Army of Thieves: Enhancing Black-Box Model Extraction via Ensemble based sample selection

https://github.com/alanxuji/delala

공식 코드

Semi-supervised Learning with Deterministic Labeling and Large Margin Projection

https://github.com/alextamkin/active-learning-pretrained-models

공식 코드

Active Learning Helps Pretrained Models Learn the Intended Task

https://github.com/alisedaghatbaf/ACTA

공식 코드

Automated Performance Testing Based on Active Deep Learning

https://github.com/allanchen95/code

공식 코드

CODE: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking

https://github.com/alteia-ai/DIAL

공식 코드

DIAL: Deep Interactive and Active Learning for Semantic Segmentation in Remote Sensing

https://github.com/amazon-science/adaptive-in-context-learning

공식 코드

Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection

https://github.com/aminparvaneh/alpha_mix_active_learning

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Active Learning by Feature Mixing

https://github.com/anahideh/FAL--Fair-Active-Learning

공식 코드

Fair Active Learning

https://github.com/andreped/NoCodeSeg

공식 코드

Code-free development and deployment of deep segmentation models for digital pathology

https://github.com/anonydoe/knowledge-aware-federated-active-learning-with-non-iid-data

공식 코드

Knowledge-Aware Federated Active Learning with Non-IID Data

https://github.com/anonymousaccount0/dbal

공식 코드

Discrepancy-Based Active Learning for Domain Adaptation

https://github.com/ansonlcy/TSceneJAL

공식 코드

TSceneJAL: Joint Active Learning of Traffic Scenes for 3D Object Detection

https://github.com/antoinedemathelin/dbal

공식 코드

Discrepancy-Based Active Learning for Domain Adaptation

https://github.com/anxiousrabbit1/active_learning_visualization_demo

공식 코드

An Interactive Visualization Tool for Understanding Active Learning

https://github.com/aolmin/active_learning_weak_sup

공식 코드

Active Learning with Weak Supervision for Gaussian Processes

https://github.com/apivich-h/init-robust-al

공식 코드

Training-Free Neural Active Learning with Initialization-Robustness Guarantees

https://github.com/ariapoy/active-learning-benchmark

공식 코드

Re-Benchmarking Pool-Based Active Learning for Binary Classification

https://github.com/arpanbiswas52/imfbo_ising

공식 코드

Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities

https://github.com/arpanbiswas52/vartbo

공식 코드

A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments

https://github.com/arthur-thuy/qde-active-learning

공식 코드

Active Learning to Guide Labeling Efforts for Question Difficulty Estimation

https://github.com/arvindmvepa/al-seg

공식 코드

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation

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