Results 41 to 50 of about 298,825 (343)
Robust 2-bit Quantization of Weights in Neural Network Modeled by Laplacian Distribution
Advances in Electrical and Computer Engineering, 2021 Significant efforts are constantly involved in finding manners to decrease the number of bits required for quantization of neural network parameters. Although in addition to compression, in neural networks, the application of quantizer models that are ...
PERIC, Z. +3 more
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Distortion Minimization Hashing
IEEE Access, 2017 Application of the hashing method to large-scale image retrieval has drawn much attention because of the high efficiency and favorable accuracy of the method.
Tongtong Yuan, Weihong Deng, Jiani Hu
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Minisuperspace Quantization of f(T, B) Cosmology
Universe, 2021 We discuss the quantization in the minisuperspace for the generalized fourth-order teleparallel cosmological theory known as fT, B. Specifically we focus on the case where the theory is linear on the torsion scalar, in that consideration we are able to ...
Andronikos Paliathanasis
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Applied Sciences, 2020 This paper is an extension of the existing works on the frequency-domain-based bit flipping control strategy for stabilizing the single-bit high-order interpolative sigma delta modulator. In particular, this paper proposes the implementation and performs
Huishan Zhai, Bingo Wing-Kuen Ling
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Quantization Dimension via Quantization Numbers
Real Analysis Exchange, 2004 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kesseböhmer, Marc, Zhu, Sanguo
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From Quantized DNNs to Quantizable DNNs
Proceedings of the British Machine Vision Conference 2020, 2020 This paper proposes Quantizable DNNs, a special type of DNNs that can flexibly quantize its bit-width (denoted as `bit modes' thereafter) during execution without further re-training. To simultaneously optimize for all bit modes, a combinational loss of all bit modes is proposed, which enforces consistent predictions ranging from low-bit mode to 32-bit
Kunyuan Du, Ya Zhang 0002, Haibing Guan
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Physical Review D, 2022 v2 matches the version accepted for publication on Phys. Rev. D. It includes additional clarifications and references. v3 includes some missing terms in a couple of equations.
Giulia Gubitosi +3 more
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IEEE Access, 2021 We consider a power constrained downlink communication scenario where energy efficiency, reliability, and latency take precedence over rate, as in some Internet of Things (IoT) applications.
Sherief Helwa, Naofal Al-Dhahir
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Product Quantization for Nearest Neighbor Search
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011 This paper introduces a product quantization-based approach for approximate nearest neighbor search. The idea is to decompose the space into a Cartesian product of low-dimensional subspaces and to quantize each subspace separately.
H. Jégou +2 more
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There is no “first” quantization [PDF]
Physics Letters A, 2003 The introduction of spinor and other massive fields by ``quantizing'' particles (corpuscles) is conceptually misleading. Only spatial fields must be postulated to form the fundamental objects to be quantized (that is, to define a formal basis for all quantum states), while apparent ``particles'' are a mere consequence of decoherence. This conclusion is
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