Results 11 to 20 of about 135,120 (295)
A Dual-Programmable 2M NOR Flash Architecture for Energy-Efficient In-Memory Computing. [PDF]
Adv Sci (Weinh)In conventional NOR Flash, the access transistor occupies area but stores no information. Here, it is repurposed as a programmable second memory device that plays two functional roles: an analog memory element that lowers the minimum read current from 72.7 nA to 4.22 pA, and a current‐path gating element enabling true‐off pruning and current‐range ...
Kim S, Ryu D, Kim H, Jung S, Kim MH.
europepmc +2 more sources
Pruning-aware Sparse Regularization for Network Pruning
Machine Intelligence Research, 2023 Structural neural network pruning aims to remove the redundant channels in the deep convolutional neural networks (CNNs) by pruning the filters of less importance to the final output accuracy. To reduce the degradation of performance after pruning, many methods utilize the loss with sparse regularization to produce structured sparsity.
Nanfei Jiang +5 more
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Search space pruning and global optimization of multiple gravity assist trajectories with deep space manoeuvers [PDF]
, 2007 This paper deals with the design of optimal multiple gravity assist trajectories with deep space manoeuvres. A pruning method which considers the sequential nature of the problem is presented.
Becerra, Victor M. +4 more
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Jmax-pruning: A facility for the information theoretic pruning of modular classification rules. [PDF]
, 2012 The Prism family of algorithms induces modular classification rules in contrast to the Top Down Induction of Decision Trees (TDIDT) approach which induces classification rules in the intermediate form of a tree structure.
Frederic Stahl +5 more
core +1 more source
To Prune or not to Prune: A Chaos-Causality Approach to Principled Pruning of Dense Neural Networks
CoRR, 2023 Reducing the size of a neural network (pruning) by removing weights without impacting its performance is an important problem for resource-constrained devices. In the past, pruning was typically accomplished by ranking or penalizing weights based on criteria like magnitude and removing low-ranked weights before retraining the remaining ones.
Rajan Sahu +4 more
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Jurnal Ilmu Pertanian Indonesia, 2020 The research to improve the growth, production, and seed quality of Jack Bean (Canavalia ensiformis L.) through pruning, which was carried out from May to October 2016 in Purwasari Village, Dramaga, Bogor Regency and continued by seed testing at the Seed
Abdulah Sarijan +3 more
doaj +1 more source
Pruning Boosts Growth, Yield, and Fruit Quality of Old Valencia Orange Trees: A Field Study
Agriculture, 2023 Pruning is an essential practice that helps control branch growth, optimize fruit size, and enhance fruit tree productivity. This study focused on ‘Valencia’ orange trees, which had experienced a decline in productivity after being cultivated on ...
Adel M. Al-Saif +6 more
doaj +1 more source
Induction of modular classification rules: using Jmax-pruning [PDF]
, 2010 The Prism family of algorithms induces modular classification rules which, in contrast to decision tree induction algorithms, do not necessarily fit together into a decision tree structure.
Frederic Stahl +5 more
core +1 more source
Effect of mechanical pruning on the yield and quality of ‘Fortune’ mandarins
Spanish Journal of Agricultural Research, 2014 This work compares mechanical pruning followed up by hand pruning versus manual pruning in the case of ‘Fortune’ mandarins. Yield and fruit quality were measured over a three-year period.
Bernardo Martin-Gorriz +2 more
doaj +1 more source
What to Prune and What Not to Prune at Initialization
CoRR, 2022 Post-training dropout based approaches achieve high sparsity and are well established means of deciphering problems relating to computational cost and overfitting in Neural Network architectures. Contrastingly, pruning at initialization is still far behind.
openaire +2 more sources