Results 11 to 20 of about 14,502,685 (316)
bioRxiv, 2021 Transcriptome profiling and differential gene expression constitute a ubiquitous tool in biomedical research and clinical application. Linear dimensionality reduction methods especially principal component analysis (PCA) are widely used in detecting ...
Yang Yang +10 more
semanticscholar +1 more source
Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality [PDF]
Operational Research, 2020 Wasserstein distributionally robust optimization is a recent emerging modeling paradigm for decision making under data uncertainty. Because of its computational tractability and interpretability, it has achieved great empirical successes across several ...
Rui Gao
semanticscholar +1 more source
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images [PDF]
AAAI Conference on Artificial Intelligence, 2019 Training an agent to solve control tasks directly from high-dimensional images with model-free reinforcement learning (RL) has proven difficult. A promising approach is to learn a latent representation together with the control policy. However, fitting a
Denis Yarats +5 more
semanticscholar +1 more source
Integral data assimilation of the MERCI-1 experiment for the nuclear data associated with the PWR decay heat computation [PDF]
EPJ Web of Conferences, 2019 Nuclear decay heat is a crucial issue for PWR in-core safety after reactor shutdown and back-end cycle. It is a dimensioning parameter for safety injection systems (SIS) to avoid a dewatering of the reactor core.
Huyghe J. +5 more
doaj +1 more source
Sample Compression, Learnability, and the Vapnik-Chervonenkis Dimension [PDF]
Machine Learning, 1995 Within the framework of pac-learning, we explore the learnability of concepts from samples using the paradigm of sample compression schemes. A sample compression scheme of size k for a concept class C ⊆ 2X consists of a compression function and a reconstruction function. The compression function receives a finite sample set consistent with some concept
Sally Floyd, Manfred K. Warmuth
openaire +3 more sources
Bitcoin price prediction using machine learning: An approach to sample dimension engineering
Journal of Computational and Applied Mathematics, 2020 After the boom and bust of cryptocurrencies’ prices in recent years, Bitcoin has been increasingly regarded as an investment asset. Because of its highly volatile nature, there is a need for good predictions on which to base investment decisions ...
Zheshi Chen, Chunhong Li, Wenjun Sun
semanticscholar +1 more source
Ciência Rural, 2010 O objetivo deste trabalho foi estimar o tamanho de amostra para avaliar caracteres de híbridos de mamoneira e verificar a variabilidade do tamanho de amostra entre híbridos e caracteres.
Alberto Cargnelutti Filho +5 more
doaj +1 more source
Ciência Rural, 2010 Os objetivos deste trabalho foram determinar o tamanho de amostra para a estimação da média de caracteres morfológicos e produtivos de crambe (Crambe abyssinica Hochst) e avaliar as relações entre esses caracteres. Foi conduzido um experimento a campo em
Alberto Cargnelutti Filho +5 more
doaj +1 more source
Energies, 2022 Renewable energy communities (REC) are bound to play a crucial role in the energy transition, as their role, activities, and legal forms become clearer, and their dissemination becomes larger.
Alexandre Lucas, Salvador Carvalhosa
doaj +1 more source
Ciência Rural, 2012 O objetivo deste trabalho foi determinar o tamanho de amostra necessário para avaliar caracteres de frutos de pêssego na colheita e após o armazenamento refrigerado. Foram colhidos frutos de um pomar comercial.
Marcos Toebe +4 more
doaj +1 more source