Weight-sharing neural architecture search: A battle to shrink the optimization gap
Neural architecture search (NAS) has attracted increasing attention. In recent years,
individual search methods have been replaced by weight-sharing search methods for higher …
individual search methods have been replaced by weight-sharing search methods for higher …
Lightweight neural architecture search for temporal convolutional networks at the edge
Neural Architecture Search (NAS) is quickly becoming the go-to approach to optimize the
structure of Deep Learning (DL) models for complex tasks such as Image Classification or …
structure of Deep Learning (DL) models for complex tasks such as Image Classification or …
Wisdom of committees: An overlooked approach to faster and more accurate models
Committee-based models (ensembles or cascades) construct models by combining existing
pre-trained ones. While ensembles and cascades are well-known techniques that were …
pre-trained ones. While ensembles and cascades are well-known techniques that were …
End-to-End Neural Network Compression via l1/l2 Regularized Latency Surrogates
Neural network (NN) compression via techniques such as pruning quantization requires
setting compression hyperparameters (eg number of channels to be pruned bitwidths for …
setting compression hyperparameters (eg number of channels to be pruned bitwidths for …
[PDF][PDF] Multiple networks are more efficient than one: Fast and accurate models via ensembles and cascades
Recent work on efficient neural network architectures focuses on discovering a solitary
network that can achieve superior computational efficiency and accuracy. While this …
network that can achieve superior computational efficiency and accuracy. While this …
D-DARTS: Distributed differentiable architecture search
Abstract Differentiable ARchiTecture Search (DARTS) is one of the most trending Neural
Architecture Search (NAS) methods. It drastically reduces search cost by resorting to weight …
Architecture Search (NAS) methods. It drastically reduces search cost by resorting to weight …
Art Design Teaching Based on the Multidata Fusion Algorithm and Virtual Simulation Technology
B Liang - Mobile Information Systems, 2022 - Wiley Online Library
Virtual Reality (VR) technologies are widely applied to teaching art design. VR has been
created with high‐level techniques that create the artificial environment to support virtual …
created with high‐level techniques that create the artificial environment to support virtual …
End-to-End Neural Network Compression via Regularized Latency Surrogates
Neural network (NN) compression via techniques such as pruning, quantization requires
setting compression hyperparameters (eg, number of channels to be pruned, bitwidths for …
setting compression hyperparameters (eg, number of channels to be pruned, bitwidths for …
Optimizing AI at the Edge: from network topology design to MCU deployment
A Burrello - 2023 - amsdottorato.unibo.it
The first topic analyzed in the thesis will be Neural Architecture Search (NAS). I will focus on
two different tools that I developed, one to optimize the architecture of Temporal …
two different tools that I developed, one to optimize the architecture of Temporal …
[PDF][PDF] Ottimizzazione automatizzata dei modelli DNN per il conteggio delle persone con sensori a infrarossi tramite NAS= Automated Optimization of DNN Models for …
S Mollaei - 2023 - webthesis.biblio.polito.it
The growing popularity of Neural Architecture Search (NAS) is changing optimization
strategies in Deep Learning (DL). While NAS has typically been utilized for tasks such as …
strategies in Deep Learning (DL). While NAS has typically been utilized for tasks such as …