Results 31 to 40 of about 9,222 (301)
A Reward Optimization Method Based on Action Subrewards in Hierarchical Reinforcement Learning
The Scientific World Journal, 2014 Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are “trial and error” and “related reward.” A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of ...
Yuchen Fu +3 more
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Cancer Informatics, 2006 Sound data analysis is critical to the success of modern molecular medicine research that involves collection and interpretation of mass-throughput data. The novel nature and high-dimensionality in such datasets pose a series of non-trivial data analysis
Constantin F. Aliferis +2 more
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High-Dimensional Brain in a High-Dimensional World: Blessing of Dimensionality
Entropy, 2020 High-dimensional data and high-dimensional representations of reality are inherent features of modern Artificial Intelligence systems and applications of machine learning.
Alexander N. Gorban +2 more
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Outlier Detection Based Feature Selection Exploiting Bio-Inspired Optimization Algorithms
Applied Sciences, 2021 The curse of dimensionality problem occurs when the data are high-dimensional. It affects the learning process and reduces the accuracy. Feature selection is one of the dimensionality reduction approaches that mainly contribute to solving the curse of ...
Souad Larabi-Marie-Sainte
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Advanced Science, EarlyView.This schematic integrates the eight statistically significant causal relationships identified between 1,366 brain imaging‐derived phenotypes (IDPs) and 18 autoimmune inflammatory diseases (AIDs). Arrows indicate the direction of causality inferred from bidirectional two‐sample MR analyses.
Jinbin Chen +8 more
wiley +1 more source
Projection Methods and the Curse of Dimensionality
Journal of Mathematical Finance, 2018 We study the ability of three different projection methods to solve high-dimensional state space problems: Galerkin, collocation, and least squares projection. The curse of dimensionality can be reduced substantially for both Least Squares and Galerkin projection methods through the use of monomial formulas.
Heer, Burkhard, Maußner, Alfred
openaire +3 more sources
Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases
Advanced Science, EarlyView.Single‐cell RNA sequencing and spatial transcriptomics have unveiled cellular heterogeneity and tissue organization with unprecedented resolution. Artificial intelligence (AI) now plays a pivotal role in interpreting these complex data. This review systematically surveys AI applications across the entire analytic workflow and offers practical guidance ...
Shixin Li +7 more
wiley +1 more source
Multi-classification for high-dimensional data using probabilistic neural networks
Journal of Radiation Research and Applied Sciences, 2022 Multi-classification tasks need sufficient information provided by the input data, whereas the input data lying in the high-dimensional space presents too sparse distributions to afford rich information, which creates trouble for multi-classification ...
Jingyi Li, Xiaojie Chao, Qin Xu
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Recent Progress in Mechanoluminescence for Multi‐Dimensional Stress Monitoring
Advanced Science, EarlyView.Multi‐dimensional stress visualization technology (0D point detection, 1D linear distribution, 2D planar imaging, 3D volume reconstruction) has become a focus of attention in the field of stress sensing. The transition from “points” to “multi‐dimensional spatial fields” facilitates real‐time, in situ, and high‐resolution visualization of stress ...
Xiuxia Yang +3 more
wiley +1 more source
Limit Theorems as Blessing of Dimensionality: Neural-Oriented Overview
Entropy, 2021 As a system becomes more complex, at first, its description and analysis becomes more complicated. However, a further increase in the system’s complexity often makes this analysis simpler.
Vladik Kreinovich, Olga Kosheleva
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