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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/llnl/gplasdi

공식 코드

Data-Driven Autoencoder Numerical Solver with Uncertainty Quantification for Fast Physical Simulations

https://github.com/lmu-dbs/diffusal

공식 코드

DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification

https://github.com/lolipopshock/Detectron2_AL

공식 코드

OLALA: Object-Level Active Learning for Efficient Document Layout Annotation

https://github.com/lorenzo-perini/ballad

공식 코드

How to Allocate your Label Budget? Choosing between Active Learning and Learning to Reject in Anomaly Detection

https://github.com/louzounlab/graph-al

공식 코드

Regional based query in graph active learning

https://github.com/lucasalegre/morl-baselines

공식 코드

Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization

https://github.com/luckeciano/bal-pm

공식 코드

Deep Bayesian Active Learning for Preference Modeling in Large Language Models

https://github.com/lucykuncheva/semi-supervised-and-constrained-clustering

공식 코드

A Bibliographic View on Constrained Clustering

https://github.com/luoxiaoheics/xal

공식 코드

XAL: EXplainable Active Learning Makes Classifiers Better Low-resource Learners

https://github.com/luoyadan/crb-active-3ddet

공식 코드

Exploring Active 3D Object Detection from a Generalization Perspective

https://github.com/lvapeab/nmt-keras

공식 코드

Active Learning for Interactive Neural Machine Translation of Data Streams

https://github.com/lyn1874/region_based_active_learning

공식 코드

On uncertainty estimation in active learning for image segmentation

https://github.com/lyumengyao/blad

공식 코드

Box-Level Active Detection

https://github.com/m0re4u/acal-subjective

공식 코드

Annotator-Centric Active Learning for Subjective NLP Tasks

https://github.com/ma921/adabatal

공식 코드

Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approach

https://github.com/machine-discovery/research

공식 코드

Reducing the Long Tail Losses in Scientific Emulations with Active Learning

https://github.com/madhavlab/2023_teles_wlc

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TeLeS: Temporal Lexeme Similarity Score to Estimate Confidence in End-to-End ASR

https://github.com/madoibito80/im2sem

공식 코드

Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning

https://github.com/mahmad00/Multiclass-AL-HSIC-using-ELM-SVM-KNN-LORSAL

공식 코드

Fuzziness-based Spatial-Spectral Class Discriminant Information Preserving Active Learning for Hyperspectral Image Classification

https://github.com/mahmad000/atl-sst

공식 코드

Spectral-Spatial Transformer with Active Transfer Learning for Hyperspectral Image Classification

https://github.com/mahsabazzaz/level-completabilty-x-active-learning

공식 코드

Active Learning for Classifying 2D Grid-Based Level Completability

https://github.com/mak-ta-reque/edgeal

공식 코드

EdgeAL: An Edge Estimation Based Active Learning Approach for OCT Segmentation

https://github.com/manuelhaussmann/ral

공식 코드

Deep Active Learning with Adaptive Acquisition

https://github.com/manueltonneau/twitter-unemployment

공식 코드

Multilingual Detection of Personal Employment Status on Twitter

https://github.com/marcovirgolin/pyNSGP

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Model Learning with Personalized Interpretability Estimation (ML-PIE)

https://github.com/marjan-nourollahi/PALS

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Proximity-Based Active Learning on Streaming Data: A Personalized Eating Moment Recognition

https://github.com/markushaug/acr-25

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Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications

https://github.com/mashijie1028/activegcd

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Active Generalized Category Discovery

https://github.com/matouk98/i-neural

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Improved Algorithms for Neural Active Learning

https://github.com/matsuo-shinnosuke/isoal

공식 코드

Instance-wise Supervision-level Optimization in Active Learning

https://github.com/mberr/ea-active-learning

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Active Learning for Entity Alignment

https://github.com/mdmustafizurrahman/An-Information-Retrieval-Approach-to-Building-Datasets-for-Hate-Speech-Detection

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An Information Retrieval Approach to Building Datasets for Hate Speech Detection

https://github.com/medicl-vu/colossal

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COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation

https://github.com/megagonlabs/tagruler

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TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration

https://github.com/meghshukla/activelearningforhumanpose

공식 코드

Bayesian Uncertainty and Expected Gradient Length -- Regression: Two Sides Of The Same Coin?

https://github.com/meghshukla/math-analysis-learningloss

공식 코드

A Mathematical Analysis of Learning Loss for Active Learning in Regression

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