Papers with Code 아카이브
Active Learning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 1
- 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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Inconsistency-Based Data-Centric Active Open-Set Annotation
Phase discovery with active learning: Application to structural phase transitions in equiatomic NiTi
Advancing Deep Active Learning & Data Subset Selection: Unifying Principles with Information-Theory Intuitions
The Role of Higher-Order Cognitive Models in Active Learning
TeLeS: Temporal Lexeme Similarity Score to Estimate Confidence in End-to-End ASR
Zero-shot Active Learning Using Self Supervised Learning
Quantifying Policy Administration Cost in an Active Learning Framework
ANALYTiC: Understanding Decision Boundaries and Dimensionality Reduction in Machine Learning
DeLR: Active Learning for Detection with Decoupled Localization and Recognition Query
Reinforcement-based Display-size Selection for Frugal Satellite Image Change Detection
Active Third-Person Imitation Learning
BAL: Balancing Diversity and Novelty for Active Learning
Optimal Decision Tree and Adaptive Submodular Ranking with Noisy Outcomes
MEAOD: Model Extraction Attack against Object Detectors
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
Entropic Open-set Active Learning
Generalized Category Discovery with Large Language Models in the Loop
Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity
Ocean Data Quality Assessment through Outlier Detection-enhanced Active Learning
Exploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation
ProCoT: Stimulating Critical Thinking and Writing of Students through Engagement with Large Language Models (LLMs)
Bayesian Estimate of Mean Proper Scores for Diversity-Enhanced Active Learning
Hierarchical Uncertainty Aggregation and Emphasis Loss for Active Learning in Object Detection
Real-time Autonomous Control of a Continuous Macroscopic Process as Demonstrated by Plastic Forming
Detecting value-expressive text posts in Russian social media
DIRECT: Deep Active Learning under Imbalance and Label Noise
Distributional Latent Variable Models with an Application in Active Cognitive Testing
Active learning with biased non-response to label requests
Fair Active Learning in Low-Data Regimes
Advancements in Content-Based Image Retrieval: A Comprehensive Survey of Relevance Feedback Techniques
Semi-supervised Active Learning for Video Action Detection
SE(3)-Invariant Multiparameter Persistent Homology for Chiral-Sensitive Molecular Property Prediction
Benchmarking of Query Strategies: Towards Future Deep Active Learning
Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding
A Review of Machine Learning Methods Applied to Video Analysis Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.