Results 81 to 90 of about 118,288 (291)

Rule-based Machine Learning Methods for Functional Prediction [PDF]

, 1995
We describe a machine learning method for predicting the value of a real-valued function, given the values of multiple input variables. The method induces solutions from samples in the form of ordered disjunctive normal form (DNF) decision rules.
Indurkhya, N., Weiss, S. M.
core   +2 more sources

Decision Tree Pruning with Privacy-Preserving Strategies

Electronics
Machine learning techniques, particularly decision trees, have been extensively utilized in Network-based Intrusion Detection Systems (NIDSs) due to their transparent, rule-based structures that enable straightforward interpretation. However, this transparency presents privacy risks, as decision trees may inadvertently expose sensitive information such
Yee Jian Chew, Shih Yin Ooi, Ying Han Pang, Zheng You Lim   +3 more
openaire   +1 more source

Unveil Fundamental Graph Properties for Neural Architecture Search

Advanced Science, EarlyView.
This paper proposes NASGraph, a graph‐based framework that represents neural architectures as graphs whose structural properties determine performance. By revealing structure–performance relationships, NASGraph enables efficient neural architecture search with significantly reduced computation.
Zhenhan Huang, Tejaswini Pedapati, Pin‐Yu Chen, Chunheng Jiang, Jianxi Gao   +4 more
wiley   +1 more source

An Information Theory-Inspired Strategy for Automated Network Pruning

International Journal of Computer Vision
Despite superior performance on many computer vision tasks, deep convolution neural networks are well known to be compressed on devices that have resource constraints. Most existing network pruning methods require laborious human efforts and prohibitive computation resources, especially when the constraints are changed.
Xiawu Zheng, Yuexiao Ma, Teng Xi, Gang Zhang, Errui Ding, Yuchao Li, Jie Chen, Yonghong Tian, Rongrong Ji   +8 more
openaire   +2 more sources

Genome‐Wide Association Study Reveals Insect Genetics and Microbial Symbiont Effects on Susceptibility of Diaphorina citri to the Citrus Greening Pathogen, Candidatus Liberibacter Asiaticus

Advanced Science, EarlyView.
This study investigates the genetic and microbial factors influencing the susceptibility of Diaphorina citri to the citrus greening pathogen Candidatus Liberibacter asiaticus (CLas), employing a microbiome Genome Wide Association Study. The research identifies a key gene encoding an MFS‐type transporter contributing to CLas infectivity and abundance in
Kai Liu, Qingcui He, Zeyue Lin, Shixuan Huang, Zichun Zhong, Pingyang Zhu, Mengge Gao, Luyao Zhao, Han Jin, Guiting Wu, Gurr M. Geoff, Qunxin Han, Rui Pang   +12 more
wiley   +1 more source

Optimizing crop loading of apples and pears - results 2004-2006 (foliar fertilizers, thinning) [PDF]

, 2008
Main topics of the research-project FuE 03OE088 of “Bundesprogramm Ökologischer Landbau” (30.04.2004-31.12.2006) were the testing of foliar fertilizers in organic apples and pears, optimizing lime sulphur for blossom thinning, looking for alternatives ...
Eis, B., Fieger-Metag, N., Pfeiffer, B., Zimmer, J.   +3 more
core  

Preemptively pruning Clever-Hans strategies in deep neural networks

Information Fusion
Robustness has become an important consideration in deep learning. With the help of explainable AI, mismatches between an explained model's decision strategy and the user's domain knowledge (e.g. Clever Hans effects) have been identified as a starting point for improving faulty models.
Lorenz Linhardt, Klaus-Robert Müller, Grégoire Montavon   +2 more
openaire   +3 more sources

Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain

Advanced Science, EarlyView.
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio, Tommaso Gili, Andrea Gabrielli, Maurizio Mattia   +3 more
wiley   +1 more source

Training Behavior of Sparse Neural Network Topologies

, 2019
Improvements in the performance of deep neural networks have often come through the design of larger and more complex networks. As a result, fast memory is a significant limiting factor in our ability to improve network performance.
Alford, Simon, Kepner, Jeremy, Milechin, Lauren, Robinett, Ryan   +3 more
core   +1 more source

Intracellular Aβ42 Sequestration by a Serine Protease Mitigates Neurotoxicity in a Drosophila Alzheimer's Disease Model

Advanced Science, EarlyView.
Emerging evidence suggests that intraneuronal Aβ accumulation represents an early pathogenic event in Alzheimer's disease (AD). Using Drosophila AD model, this study shows that a nonsecreted serine protease Yip7 physically interacts with Aβ. This causes intraneuronal Aβ accumulation but surprisingly reduces the associated neurotoxicity, arguing that ...
Jingyun Su, Meng Yang, Xinfeng Wang, Pa Wu, Zongzhao Zhai   +4 more
wiley   +1 more source