Examples of 'computationally expensive' in a sentence
Meaning of "computationally expensive"
computationally expensive: Refers to tasks, processes, or operations that require a significant amount of computational resources, such as time and/or energy
How to use "computationally expensive" in a sentence
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computationally expensive
Neural network training is a computationally expensive task.
This is computationally expensive and undesirable.
Processing mission functions can be computationally expensive.
It can be computationally expensive to solve the linear regression problems.
Level set methods can be computationally expensive.
This produces a computationally expensive aircraft performance evaluation process.
This makes this technique very computationally expensive.
Either computationally expensive or infeasible.
The optimal approach is computationally expensive.
Wrappers can be computationally expensive and have a risk of over fitting to the model.
Calculation of the modulation signal can be computationally expensive.
This method is computationally expensive due to the large number of samples.
Another is that processing these databases is very computationally expensive.
The method is less computationally expensive due to having a fewer samples.
A full search of all potential blocks however is a computationally expensive task.
See also
This translation can be computationally expensive and benefits from hardware acceleration.
This rounding rule is more accurate but more computationally expensive.
Zcash is more computationally expensive but comes with more rigorous security properties.
Or the algorithm is to computationally expensive.
This is computationally expensive to achieve, but computationally simple to verify.
Higher degree curves are more computationally expensive to evaluate.
In a model of a complex systems of neurons, numerical integration of the equations are computationally expensive.
The two codes are computationally expensive.
Traditional system identification methods for nonlinear systems are often computationally expensive.
This is complex and computationally expensive.
Conventionally, hysteresis is neglected in electromagnetic simulations, as its inclusion is complicated and computationally expensive.
Such chains can be computationally expensive.
As these problems involve repeated numerical simulations, most often they are quite computationally expensive.
This is a potentially computationally expensive procedure.
Full strong branching tests all candidate variables and can be computationally expensive.
ZKP is computationally expensive.
Generally this analysis is performed via computationally expensive simulations.
This is the most computationally expensive step ; the systems involve sparse and ill conditioned matrices.
Surrogate models approximate the multivariate behaviour of systems using a limited number of computationally expensive simulations.
Therefore, it is more computationally expensive to evaluate their structures.
When n is large, HatMatrix might be computationally expensive.
Many of these problems are computationally expensive and require high-performance implementations.
Further, the use of prediction models is computationally expensive.
However, large networks are computationally expensive in terms of the training and inference time.
However, due to the required complexity, it is still to computationally expensive.
However, it is computationally expensive.
However, echo cancellers suffer from stability problems and are computationally expensive.
However, this is computationally expensive.
Performing a ray / polygon intersection test with each would be a very computationally expensive task.
Calculating the interpolating polynomial is computationally expensive (see computational complexity) compared to linear interpolation.
Without the source code for a particular piece of software, portability is generally computationally expensive.
The factorization step is the most computationally expensive step in the algorithm.
This results in high coverage, but the assembly process is much more computationally expensive.
Many volume visualization algorithms are computationally expensive and demand large data storage.
Nevertheless, the coupling of three-dimensional radiative transfer with fluid dynamics is very computationally expensive.
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Computationally that can be a really difficult thing to do
There is still not a computationally satisfactory approach
Computationally more efficient algorithms to solve equations eq
