Results 21 to 30 of about 10,276 (261)
Computational Linguistics, 2021 AbstractThe transcription bottleneck is often cited as a major obstacle for efforts to document the world’s endangered languages and supply them with language technologies. One solution is to extend methods from automatic speech recognition and machine translation, and recruit linguists to provide narrow phonetic transcriptions and sentence-aligned ...
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Frontiers in Computational Neuroscience, 2018 Humans have flexible control over cognitive functions depending on the context. Several studies suggest that the prefrontal cortex (PFC) controls this cognitive flexibility, but the detailed underlying mechanisms remain unclear.
Satoshi Kuroki +2 more
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IEEE Access, 2021 In active sonar systems, detection always suffers from reverberation interference from multiple scatterers in oceanic environments; therefore, numerous studies have been conducted on reverberation suppression.
Geunhwan Kim, Seokjin Lee
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Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization
IEEE Access, 2018 Nonsmooth nonnegative matrix factorization (nsNMF) is capable of producing more localized, less overlapped feature representations than other variants of NMF while keeping satisfactory fit to data. However, nsNMF as well as other existing NMF methods are
Jinshi Yu +3 more
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2020 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), 2020 MP4 is currently the gold standard for video compression. Here we demonstrate that MP4 can be augmented by using a spatiotemporal sparse code optimized for the reconstruction of video portraits to up-sample data streams in which 75% of the pixels have been removed.
Daniel A. Wang +5 more
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Frontiers in Synaptic Neuroscience, 2014 Long-term synaptic plasticity is fundamental to learning and network function. It has been studied under various induction protocols and depends on firing rates, membrane voltage, and precise timing of action potentials.These protocols show different ...
Daniel eKrieg, Jochen eTriesch
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An Adaptive Homeostatic Algorithm for the Unsupervised Learning of Visual Features
Vision, 2019 The formation of structure in the visual system, that is, of the connections between cells within neural populations, is by and large an unsupervised learning process.
Laurent U. Perrinet
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Factors of Sparse Polynomials are Sparse.
Electron. Colloquium Comput. Complex., 2014 This paper was removed due to an error in the proof (Claim 4.12 as stated is not true)
Zeev Dvir, Rafael Oliveira 0002
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Sparse-to-Sparse Training of Diffusion Models [PDF]
CoRRDiffusion models (DMs) are a powerful type of generative models that have achieved state-of-the-art results in various image synthesis tasks and have shown potential in other domains, such as natural language processing and temporal data modeling.
OLIVEIRA, Inês +2 more
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Stabilized Sparse Online Learning for Sparse Data
J. Mach. Learn. Res., 2016 45 pages, 4 ...
Yuting Ma, Tian Zheng
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