SparseNN: A Performance-Efficient Accelerator for Large-Scale Sparse Neural Networks
Sign Up to like & getrecommendations! Published in 2017 at "International Journal of Parallel Programming"
DOI: 10.1007/s10766-017-0528-8
Abstract: Neural networks have been widely used as a powerful representation in various research domains, such as computer vision, natural language processing, and artificial intelligence, etc. To achieve better effect of applications, the increasing number of… read more here.
Keywords: neural networks; sparsenn performance; sparse neural; performance efficient ... See more keywords
Pre-Defined Sparse Neural Networks With Hardware Acceleration
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Journal on Emerging and Selected Topics in Circuits and Systems"
DOI: 10.1109/jetcas.2019.2910864
Abstract: Neural networks have proven to be extremely powerful tools for modern artificial intelligence applications, but computational and storage complexity remain limiting factors. This paper presents two compatible contributions towards reducing the time, energy, computational, and… read more here.
Keywords: defined sparse; hardware acceleration; pre defined; neural networks ... See more keywords
Sparse neural network regression with variable selection
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence"
DOI: 10.1111/coin.12557
Abstract: This paper reports on our study of a sparse neural network regression method based on a single hidden layer architecture and sparsity‐inducing penalties. To determine the size of network in a data‐adaptive way, we adopt… read more here.
Keywords: neural network; network; regression variable; sparse neural ... See more keywords
Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cells
Sign Up to like & getrecommendations! Published in 2018 at "eLife"
DOI: 10.7554/elife.33503
Abstract: A goal of systems neuroscience is to discover the circuit mechanisms underlying brain function. Despite experimental advances that enable circuit-wide neural recording, the problem remains open in part because solving the ‘inverse problem’ of inferring… read more here.
Keywords: perturbation; neural recording; circuit; sparse neural ... See more keywords