Examples of using Approximation in English and their translations into Chinese
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Political
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Ecclesiastic
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Programming
Approximation Methods(i.e. how to plug in a deep neural network or other differentiable model into your RL algorithm).
The following rough approximation, based on unofficial estimates, gives some sense of the scale and gravity of these crimes.
Some polynomial sequences arise in physics and approximation theory as the solutions of certain ordinary differential equations.
On the other hand, the gradient approximation which it produces is relatively crude, in particular for high frequency variations in the image.
The value returned is an approximation, however, because it does not account for leap years and assumes only 30 days per month.
Kernel-based methods involve fundamental approximation theory(mathematics), stochastic analysis(statistics) and various applications from data science and machine learning.
We know now from the Universal Approximation Theorem that any large enough neural network can approximate any arbitrarily complex function.
KL Divergence helps us to measure just how much information we lose when we choose an approximation.
And in another passage, Lenin noted:“Cognition is the eternal, endless approximation of thought to the object.
In it, they introduced the random phase approximation(RPA), now widely used in many-body physics.
This is the second-order Taylor approximation, but we could increase the accuracy by adding even higher-order derivatives.
While Armenia considered the data to be an approximation, it would not be possible to obtain more accurate data for that year.
According to the depletion approximation condition, the carrier concentration at the boundary of the depletion region is approximately 0, that is, p=n=0.
However, there are various approximation methods that can help us to represent the complex quantum correlations between the electrons," according to Held.
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In this work, Gauss used comprehensive approximation methods which he created for that purpose.
A deep feedforward network can be defined as a mapping y= f(x;θ), which learns the parameters θ to obtain the best function approximation.
This approximation allows us to reformulate the t-SNE minimization problem as a series of tensor operations that can be efficiently executed on the graphics card.
Symbol consists of Numbers,(b) part of the lamp holder main dimensions of approximation, it said the unit is mm.
Then the differential of φ at a point x is, in some sense, the best linear approximation of φ near x….