Zobrazeno 1 - 10
of 250
pro vyhledávání: '"Eguchi Shinto"'
Principal component analysis (PCA) is a widely used technique for dimension reduction. As datasets continue to grow in size, distributed-PCA (DPCA) has become an active research area. A key challenge in DPCA lies in efficiently aggregating results ac
Externí odkaz:
http://arxiv.org/abs/2410.00397
Autor:
Eguchi, Shinto
The book is structured into four main chapters. Chapter 1 introduces the foundational concepts of divergence measures, including the well-known Kullback-Leibler divergence and its limitations. It then presents a detailed exploration of power divergen
Externí odkaz:
http://arxiv.org/abs/2408.01893
Species distribution modeling plays an important role in estimating the habitat suitability of species using environmental variables. For this purpose, Maxent and the Poisson point process are popular and powerful methods extensively employed across
Externí odkaz:
http://arxiv.org/abs/2405.14456
Species distribution modeling (SDM) plays a crucial role in investigating habitat suitability and addressing various ecological issues. While likelihood analysis is commonly used to draw ecological conclusions, it has been observed that its statistic
Externí odkaz:
http://arxiv.org/abs/2306.17386
We discuss species distribution models (SDM) for biodiversity studies in ecology. SDM plays an important role to estimate abundance of a species based on environmental variables that are closely related with the habitat of the species. The resultant
Externí odkaz:
http://arxiv.org/abs/2304.14567
Autor:
Hino, Hideitsu, Eguchi, Shinto
Active learning is a widely used methodology for various problems with high measurement costs. In active learning, the next object to be measured is selected by an acquisition function, and measurements are performed sequentially. The query by commit
Externí odkaz:
http://arxiv.org/abs/2211.10013
Autor:
Eguchi, Shinto
This paper aims at presenting a new application of information geometry to reinforcement learning focusing on dynamic treatment resumes. In a standard framework of reinforcement learning, a Q-function is defined as the conditional expectation of a re
Externí odkaz:
http://arxiv.org/abs/2211.08741
Principal component analysis (PCA) is one of the most popular dimension reduction methods. The usual PCA is known to be sensitive to the presence of outliers, and thus many robust PCA methods have been developed. Among them, the Tyler's M-estimator i
Externí odkaz:
http://arxiv.org/abs/2206.03662
Publikováno v:
In Ecological Informatics July 2024 81
