Results 41 to 50 of about 10,276 (261)

JLGBMLoc—A Novel High-Precision Indoor Localization Method Based on LightGBM

Sensors, 2021
Wi-Fi based localization has become one of the most practical methods for mobile users in location-based services. However, due to the interference of multipath and high-dimensional sparseness of fingerprint data, with the localization system based on ...
Lu Yin, Pengcheng Ma, Zhongliang Deng
doaj   +1 more source

Back-Propagation Learning in Deep Spike-By-Spike Networks

Frontiers in Computational Neuroscience, 2019
Artificial neural networks (ANNs) are important building blocks in technical applications. They rely on noiseless continuous signals in stark contrast to the discrete action potentials stochastically exchanged among the neurons in real brains. We propose
David Rotermund, Klaus R. Pawelzik
doaj   +1 more source

Evaluation of a library of loxP variants with a wide range of recombination efficiencies by Cre.

PLoS ONE, 2022
Sparse labeling of individual cells is an important approach in neuroscience and many other fields of research. Various methods have been developed to sparsely label only a small population of cells; however, there is no simple and reproducible strategy ...
Yuji Yamauchi, Hidenori Matsukura, Keisuke Motone, Mitsuyoshi Ueda, Wataru Aoki   +4 more
doaj   +1 more source

Sparse Cointegration

SSRN Electronic Journal, 2014
Cointegration analysis is used to estimate the long-run equilibrium relations between several time series. The coefficients of these long-run equilibrium relations are the cointegrating vectors. In this paper, we provide a sparse estimator of the cointegrating vectors.
Wilms, Ines, Croux, Christophe
openaire   +2 more sources

Adaptive sparse tiling for sparse matrix multiplication [PDF]

Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming, 2019
Tiling is a key technique for data locality optimization and is widely used in high-performance implementations of dense matrix-matrix multiplication for multicore/manycore CPUs and GPUs. However, the irregular and matrix-dependent data access pattern of sparse matrix multiplication makes it challenging to use tiling to enhance data reuse.
Changwan Hong, Aravind Sukumaran-Rajam, Israt Nisa, Kunal Singh, P. Sadayappan   +4 more
openaire   +1 more source

Kernel heterogeneity improves sparseness of natural images representations

Neuromorphic Computing and Engineering
Both biological and artificial neural networks inherently balance their performance with their operational cost, which characterizes their computational abilities.
Hugo J Ladret, Christian Casanova, Laurent Udo Perrinet   +2 more
doaj   +1 more source

Sparse Warcasting

Scottish Journal of Political Economy, 2023
ABSTRACT Forecasting economic activity during institutional collapse requires nowcasts derived exclusively from alternative data sources. Such sources are abundant yet theoretically unanchored and potentially weakly informative. This study examines whether sparse supervised dimension reduction extracts reliable signals in a context ...
openaire   +2 more sources

European Standard Clinical Practice Guideline and EXPeRT Recommendations for the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms in Children and Adolescents

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen, Calogero Virgone, Antje Redlich, Michael Abele, Ricardo Lopez‐Almaraz, Tal Ben‐Ami, Ewa Bien, Gianni Bisogno, Maja Mazic Cesen, Andrea Ferrari, Malgorzata A. Krawczyk, Yves Reguerre, Dominik T. Schneider, Ines B. Brecht, Charlotte Rigaud, Bilgehan Yalcin, Rainer Claus, Christian Vokuhl, Constantin Lapa, Jörg Fuchs, Segolene Hescot, Thomas Walter, Julien Hadoux, Daniel Orbach   +23 more
wiley   +1 more source

Nonnegative Matrix Factorization With Data-Guided Constraints For Hyperspectral Unmixing

Remote Sensing, 2017
Hyperspectral unmixing aims to estimate a set of endmembers and corresponding abundances in pixels. Nonnegative matrix factorization (NMF) and its extensions with various constraints have been widely applied to hyperspectral unmixing.
Risheng Huang, Xiaorun Li, Liaoying Zhao
doaj   +1 more source

Central Nervous System Neuroblastoma, FOXR2‐Activated: A Pooled Analysis of Published Clinical Outcomes

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Central nervous system (CNS) neuroblastoma, FOXR2‐activated, is a recently recognized entity in the WHO CNS5 classification, defined by activation of the FOXR2 transcription factor and unique histopathological features. This review synthesizes available literature and pooled clinical data, providing insight into demographics ...
Sudarshawn Damodharan, Mohamed S. Abdelbaki   +1 more
wiley   +1 more source