Results 251 to 260 of about 31,077 (302)

Energy-Adaptive Multi-Dimensional Learning Control for Federated Learning in Energy-Harvesting AIoT Systems. [PDF]

Sensors (Basel)
Noh DK, Kwak C.
europepmc   +1 more source

Symptom-Level Precision Neurology in Amyotrophic Lateral Sclerosis (ALS): Linking Microglial Pruning, Mitochondrial Nicotinamide Adenine Dinucleotide (NAD+) Compensation, and Autophagy Failure Across the Aging Spectrum. [PDF]

Cureus
Cheung N.
europepmc   +1 more source

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A new strategy for skeleton pruning

Pattern Recognition Letters, 2016
A new pruning algorithm is introduced to simplify the structure of the skeleton of 2D objects, without affecting significantly the representative power of the skeleton. The concatenations of skeleton branches originating from the end points of the skeleton are examined while building a hierarchical skeleton structure.
Luca Serino, Gabriella Sanniti Di Baja
exaly   +3 more sources

Multi-Objective Workflow Optimization Algorithm Based on a Dynamic Virtual Staged Pruning Strategy

Processes, 2023
Time, cost, and quality are critical factors that impact the production of intelligent manufacturing enterprises. Achieving optimal values of production parameters is a complex problem known as an NP-hard problem, involving balancing various constraints.
Zhiyong Luo, Haifeng Xu, Jiahui Liu, Xintong Liu, Shanxin Tan   +4 more
exaly   +2 more sources

Pruning strategies for mixed-mode querying

Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06, 2006
Web information retrieval systems face a range of unique challenges, not the least of which is the sheer scale of the data that must be handled. Also specific to web retrieval is that queries may be a mix of Boolean and ranked features, and documents may have static score components that must also be factored into the ranking process.
Vo Ngoc Anh, Alistair Moffat
openaire   +1 more source

An empirical comparison of pruning strategies in game trees

IEEE Transactions on Systems, Man, and Cybernetics, 1985
Size pruning strategies on uniform and nonuniform game trees of 24 different sizes, each being assigned leaf-node static values under four different schemes, are compared. The performance of these strategies is compared on the basis of nodes created, node visits, and CPU time.
Agata Muszycka, Rajjan Shinghal
openaire   +1 more source

Pruning strategies for the MTiling constructive learning algorithm

Proceedings of International Conference on Neural Networks (ICNN'97), 2002
We present a framework for incorporating pruning strategies in the MTiling constructive neural network learning algorithm. Pruning involves elimination of redundant elements (connection weights or neurons) from a network and is of considerable practical interest.
Rajesh Parekh, Jihoon Yang, Vasant G. Honavar   +2 more
openaire   +1 more source

Prune Strategy to YOLO-Based Model

2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI), 2020
One-stage networks have been widely used in target detection systems that need to learn from the big data. Most of them have good real-time performance and accuracy. However, due to their convolution structure, in actual applications, they still require more memory space and stronger computing power, thereby we choose to apply a pruning strategy on the
Boyu Zhao, Zhicheng Dong, Xuerui Zhang, Jie Li   +3 more
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Specification Issues and Pruning Strategies

1998
In this chapter, several issues concerning input specification representation and preprocessing steps for the actual DTSE methodology will be briefly discussed. These issues become much more complex when applied to practical designs, but in the scope of the book they cannot be presented in more detail.
Francky Catthoor, Sven Wuytack, Eddy De Greef, Florin Balasa, Lode Nachtergaele, Arnout Vandecappelle   +5 more
openaire   +1 more source

Pruning strategies for nearest neighbor competence preservation learners

Neurocomputing, 2018
Abstract In order to alleviate both the spatial and temporal cost of the nearest neighbor classification rule, competence preservation techniques aim at substituting the training set with a selected subset, known as consistent subset. In order to improve generalization and to prevent induction of overly complex models, in this study the application ...
Fabrizio Angiulli, Estela Narvaez
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