arXiv:1710.00379
공식 코드 · Papers with Code
libact: Pool-based Active Learning in Python
원문 초록
libact is a Python package designed to make active learning easier for general users. The package not only implements several popular active learning strategies, but also features the active-learning-by-learning meta-algorithm that assists the users to automatically select the best strategy on the fly. Furthermore, the package provides a unified interface for implementing more strategies, models and application-specific labelers. The package is open-source on Github, and can be easily installed from Python Package Index repository.
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Near-Polynomially Competitive Active Logistic Regression
CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization
Active Learning for Manifold Gaussian Process Regression
The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning
Info-Coevolution: An Efficient Framework for Data Model Coevolution
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
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