by instadatahelp | Sep 6, 2023 | AI Blogs
A Comprehensive Definition of Redundancy and Relevance in Feature Selection Based on Information Decomposition Patricia Wollstadt, Sebastian Schmitt, Michael Wibral; 24(131):1−44, 2023. Abstract In machine learning and statistics, the selection of a minimal set of...
by instadatahelp | Sep 6, 2023 | AI Blogs
We present a new approach to enhance the performance of trading strategies developed through deep reinforcement learning algorithms in the highly unpredictable environment of intraday cryptocurrency portfolio trading. Our method involves using an ensemble technique to...
by instadatahelp | Sep 6, 2023 | AI Blogs
On the Relationship Between Distance and Kernel Measures of Conditional Dependence Tianhong Sheng, Bharath K. Sriperumbudur; 24(7):1−16, 2023. Abstract Measuring conditional dependence is a crucial task in statistical inference and plays a fundamental role in various...
by instadatahelp | Sep 6, 2023 | AI Blogs
In the realm of finance, accurately predicting stock market trends has always been a formidable challenge. However, with the emergence of machine learning as a powerful tool for forecasting, this research paper undertakes a comparative analysis of four machine...
by instadatahelp | Sep 6, 2023 | AI Blogs
Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data Di Wang, Lijie Hu, Huanyu Zhang, Marco Gaboardi, Jinhui Xu; 24(132):1−57, 2023. Abstract This paper examines the estimation of smooth Generalized Linear Models (GLMs) in the...
by instadatahelp | Sep 6, 2023 | AI Blogs
Sampling Random Graph Homomorphisms and Its Applications in Network Data Analysis Hanbaek Lyu, Facundo Memoli, David Sivakoff; 24(9):1−79, 2023. Abstract A graph homomorphism refers to a mapping between two graphs that preserves adjacency relations. This study focuses...
