Results 41 to 50 of about 2,045,405 (349)
A stepwise emergence of evolution in the RNA world
FEBS Letters, EarlyView.How did biological evolution emerge from chemical reactions? This perspective proposes a gradual scenario of self‐organization among RNA molecules, where catalytic feedback on random mixtures plays the central role. Short oligomers cross‐ligate, and self‐assembly enables heritable variations. An event of template‐externalization marks the transition to
Philippe Nghe
wiley +1 more source
A review of problem- and team-based methods for teaching statistics in Higher Education [PDF]
, 2019 The teaching of statistics in higher education in the UK is still largely lecture-based. This is despite recommendations such as those given by the American Statistical Association's GAISE report that more emphasis should be placed on active learning strategies where students take more responsibility for their own learning.
arxiv +1 more source
, 2020 This mixed research aims to analysis and design the Web Game On Descriptive Statistics (WGODS) through the ADDIE model, data science and machine learning. The sample consists of 61 students from a university in Mexico. WGODS is a technological tool (quiz
R. Salas-Rueda +2 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Statistical Mechanics of Time Domain Ensemble Learning [PDF]
, 2006 Conventional ensemble learning combines students in the space domain. On the other hand, in this paper we combine students in the time domain and call it time domain ensemble learning. In this paper, we analyze the generalization performance of time domain ensemble learning in the framework of online learning using a statistical mechanical method.
arxiv +1 more source
Retarded Learning: Rigorous Results from Statistical Mechanics [PDF]
Phys. Rev. Lett. 86(10), pp. 2174-2177, 2001, 2001 We study learning of probability distributions characterized by an unknown symmetry direction. Based on an entropic performance measure and the variational method of statistical mechanics we develop exact upper and lower bounds on the scaled critical number of examples below which learning of the direction is impossible. The asymptotic tightness of the
arxiv +1 more source
Molecular Oncology, EarlyView.Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
wiley +1 more source
Online Learning for Statistical Machine Translation [PDF]
Computational Linguistics, 2016 We present online learning techniques for statistical machine translation (SMT). The availability of large training data sets that grow constantly over time is becoming more and more frequent in the field of SMT—for example, in the context of translation agencies or the daily translation of government proceedings.
openaire +3 more sources
Machine learning, statistical learning and the future of biological research in psychiatry [PDF]
Psychological Medicine, 2016 Psychiatric research has entered the age of ‘Big Data’. Datasets now routinely involve thousands of heterogeneous variables, including clinical, neuroimaging, genomic, proteomic, transcriptomic and other ‘omic’ measures. The analysis of these datasets is challenging, especially when the number of measurements exceeds the number of individuals, and may ...
Iniesta, R.; Stahl, D.; McGuffin, P.
openaire +6 more sources
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets [PDF]
, 1997 This paper introduces new algorithms and data structures for quick counting for machine learning datasets. We focus on the counting task of constructing contingency tables, but our approach is also applicable to counting the number of records in a ...
Lee, M. S., Moore, A.
core +3 more sources