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Found 5 papers, 1 papers with code
Metaheuristic Algorithms in Artificial Intelligence with Applications to Bioinformatics, Biostatistics, Ecology and, the Manufacturing Industries
Nature-inspired metaheuristic algorithms are important components of artificial intelligence, and are increasingly used across disciplines to tackle various types of challenging optimization problems.
Trajectory-aware Principal Manifold Framework for Data Augmentation and Image Generation
Many existing methods generate new samples from a parametric distribution, like the Gaussian, with little attention to generate samples along the data manifold in either the input or feature space.
A Roadmap to Asymptotic Properties with Applications to COVID-19 Data
Asymptotic properties of statistical estimators play a significant role both in practice and in theory.
Dual Path Structural Contrastive Embeddings for Learning Novel Objects
Learning novel classes from a very few labeled samples has attracted increasing attention in machine learning areas.
Projection Pursuit with Applications to scRNA Sequencing Data
In this paper, we explore the limitations of PCA as a dimension reduction technique and study its extension, projection pursuit (PP), which is a broad class of linear dimension reduction methods.
