Results 31 to 40 of about 6,198,210 (289)
Neural Architecture Search for Keyword Spotting [PDF]
Interspeech 2020, 2020 Deep neural networks have recently become a popular solution to keyword spotting systems, which enable the control of smart devices via voice. In this paper, we apply neural architecture search to search for convolutional neural network models that can help boost the performance of keyword spotting based on features extracted from acoustic signals ...
Tong Mo +4 more
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Neural Architecture Search for Transformers: A Survey
IEEE Access, 2022 Transformer-based Deep Neural Network architectures have gained tremendous interest due to their effectiveness in various applications across Natural Language Processing (NLP) and Computer Vision (CV) domains.
Krishna Teja Chitty-Venkata +3 more
doaj +1 more source
Symbolic Neural Architecture Search for Differential Equations
IEEE Access, 2023 In this paper, we introduce the first use of symbolic integration that leverages the machine learning infrastructure, such as automatic differentiation, to find analytical approximations of ordinary and partial differential equations.
Paulius Sasnauskas, Linas Petkevicius
doaj +1 more source
APNAS: Accuracy-and-Performance-Aware Neural Architecture Search for Neural Hardware Accelerators
IEEE Access, 2020 Designing resource-efficient deep neural networks (DNNs) is a challenging task due to the enormous diversity of applications as well as their time-consuming design, training, optimization, and evaluation cycles, especially the resource-constrained ...
Paniti Achararit +4 more
doaj +1 more source
Hierarchical quantum circuit representations for neural architecture search
npj Quantum Information, 2023 Quantum circuit algorithms often require architectural design choices analogous to those made in constructing neural and tensor networks. These tend to be hierarchical, modular and exhibit repeating patterns.
Matt Lourens +4 more
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Efficient Neural Architecture Search using Genetic Algorithm [PDF]
, 2022 NASNet and AmoebaNet are state-of-the-art neural architecture search systems that were able to achieve better accuracy than state-of-the-art human-made convolutional neural networks.
Morgan, Brandon
core
DistilNAS: Neural Architecture Search With Distilled Data
IEEE Access, 2022 Can we perform Neural Architecture Search (NAS) with a smaller subset of target dataset and still fair better in terms of performance with significant reduction in search cost?
Swaroop N. Prabhakar +3 more
doaj +1 more source
Neural Architecture Search for Skin Lesion Classification
IEEE Access, 2020 Deep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture.
Arkadiusz Kwasigroch +2 more
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Conditional Neural Architecture Search
CoRR, 2020 Designing resource-efficient Deep Neural Networks (DNNs) is critical to deploy deep learning solutions over edge platforms due to diverse performance, power, and memory budgets. Unfortunately, it is often the case a well-trained ML model does not fit to the constraint of deploying edge platforms, causing a long iteration of model reduction and ...
Sheng-Chun Kao +3 more
openaire +2 more sources
Topology-Sensitive Neural Architecture Search for Language Modeling
IEEE Access, 2021 Recently Neural Architecture Search has drawn interest from researchers because of its ability to learn neural network architectures from data automatically.
Quan Du +4 more
doaj +1 more source