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How much did Keanu Reeves make for Matrix Reloaded? 

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Proceedings ArticleDOI
Xu Xiang, Yanmin Qian, Kai Yu 
20 Aug 2017
26 Citations
This results in much faster DNN inference since matrix multiplication is the most computationally expensive operation.
The momentous copulating of Trinity and Neo in Matrix Reloaded, I argue, offers both the characters and cinemagoers the promise of the birth of freedom from the white loins of the characters.
This shows that the differential properties in the matrix case are much more complicated than in the scalar situation.
Proceedings ArticleDOI
Nan Chen, Peikang Wang 
01 Nov 2018
39 Citations
This encoder-decoder framework is used to reconstruct the input matrix, this process of the reconstruction of input matrix by decoder makes the features learning in CNN much more intrinsic and effective.
Random linear code-based matrix embedding can achieve high embedding efficiency but cost much in computation.
Results indicated that larger matrices evoked a larger P300 amplitude, and that matrix size did not significantly affect performance or preferences.
Open accessJournal ArticleDOI
Dongpo Xu, Danilo P. Mandic 
73 Citations
Illustrative examples show how the proposed quaternion matrix derivatives can be used as an important tool for solving optimization problems in signal processing applications.

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How do different environmental and operational factors impact the steady-state and time series analysis of district heating systems?
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Different environmental and operational factors have an impact on the steady-state and time series analysis of district heating systems. The use of energy conversion units like combined heat and power leads to interplays between electricity, gas, and heating systems, which can affect the operation of all other systems. Ignoring thermal dynamics in district heating systems may lead to overconservative reliability evaluation, as short-term heat interruption has less impact than long-term outage. The transient behavior of the network and thermal losses should be considered in investment or dispatch models to avoid erroneous results. The proposed multi-objective optimization framework for low-temperature district heating with booster heat pumps can reduce costs and emissions, but its viability depends on factors such as fuel type, electricity price, emission factor, and weight of costs and emissions in the objective function. The holomorphic embedding method can be used to solve the steady-state flow problem of district heating systems, providing a valid alternative to the conventional Newton-Raphson method.
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There are no studies following geb by Channon in the provided abstracts.