CR-DARTS: Channel Redistribution-Based Differentiable Architecture Search
IEEE AccessDifferentiable Architecture Search (DARTS) has shown promising results in automating the design of deep learning models. However, its search process is computationally expensive because it evaluates all candidate operations simultaneously, often leading ...
Ali Hassan +3 more
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Differentiable Architecture Search Based on Coordinate Descent
IEEE Access, 2021 Neural architecture search (NAS) is an automated method searching for the optimal network architecture by optimizing the combinations of edges and operations.
Pyunghwan Ahn +2 more
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IEEE Access, 2022 We present a Model Uncertainty-aware Differentiable ARchiTecture Search ( $\mu $ DARTS) that optimizes neural networks to simultaneously achieve high accuracy and low uncertainty. We introduce concrete dropout within DARTS cells and include a Monte-Carlo
Biswadeep Chakraborty +1 more
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DE-DARTS: Neural architecture search with dynamic exploration
ICT Express, 2023 Neural architecture search (NAS) methods automatically find optimal neural networks without human assistance. Numerous algorithms for NAS have been studied to find architectures with gradient-based search.
Jiwoo Mun, Seokhyeon Ha, Jungwoo Lee
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NDARTS: A Differentiable Architecture Search Based on the Neumann Series
Algorithms, 2023 Neural architecture search (NAS) has shown great potential in discovering powerful and flexible network models, becoming an important branch of automatic machine learning (AutoML).
Xiaoyu Han +3 more
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EEG-Based Emotion Estimation Model Integrating Structural and Time-Series Information Based on Deep Learning Architecture Optimization [PDF]
SensorsEmotion recognition is increasingly important for applications in mental health and personalized marketing. Traditional methods based on facial and vocal cues lack robustness due to voluntary control, motivating the use of EEG signals that capture neural
Kota Tsuji, Keiko Ono, Takuya Futagami
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Multi-Layer AI Sensor System for Real-Time GPS Spoofing Detection and Encrypted UAS Control [PDF]
SensorsUnmanned Aerial Systems (UASs) are playing an increasingly critical role in both civilian and defense applications. However, their heavy reliance on unencrypted Global Navigation Satellite System (GNSS) signals, particularly GPS, makes them highly ...
Ayoub Alsarhan +7 more
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Machine learning via DARTS-Optimized MobileViT models for pancreatic Cancer diagnosis with graph-based deep learning [PDF]
BMC Medical Informatics and Decision MakingThe diagnosis of pancreatic cancer presents a significant challenge due to the asymptomatic nature of the disease and the fact that it is frequently detected at an advanced stage.
Yusuf Alaca
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Event Classification with Multi-step Machine Learning [PDF]
EPJ Web of Conferences, 2021 The usefulness and value of Multi-step Machine Learning (ML), where a task is organized into connected sub-tasks with known intermediate inference goals, as opposed to a single large model learned end-to-end without intermediate sub-tasks, is presented ...
Saito Masahiko +8 more
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RARTS: An Efficient First-Order Relaxed Architecture Search Method
IEEE Access, 2022 Differentiable architecture search (DARTS) is an effective method for data-driven neural network design based on solving a bilevel optimization problem.
Fanghui Xue, Yingyong Qi, Jack Xin
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