This combination of choices of method, representation and formulation makes it difficult to predict which combination may be best.This paper presents an example from process engineering, the design of heat exch
Design and Implementation of Automatic Machine Translation Model Based on Deep Learning Algorithm As existing machine translation (MT) mainly uses rules or statistical models, it is not effective in dealing with complex languages and diverse contexts, and it is difficult to cope with low-resource ...
We review the Structure-Mapping theory and describe the design of the engine. We analyze the complexity of the algorithm, and demonstrate that most of the steps are polynomial, typically bounded by theta (N sq.) We demonstrate some examples of its operation taken from our cognitive simulation ...
In this work the fundamental limits to computation with respect to manufacturing, energy, physical space, design and verification effort, and algorithms are reviewed. As it is concluded in the paper, engineering difficulties encountered by emerging technologies may indicate yet-unknown limits. In [289...
Designing fast and accurate algorithms requires high-level abstract reasoning, which remains difficult for AI systems. Our approach involves having the AI design and solve its own programming challenges, enabling practice on millions of artificial challenges and exploration of problem types not found in...
Below, we give our analysis of the types of errors in the noisy labels, core mechanisms to handle these errors, and guidelines on how to design a DNN model with proper learning objectives and training procedures to achieve a successful learning procedure when dealing with noisy labels. ...
The design of the controller gains for the longitudinal channel of an autonomous helicopter model is formulated and solved as a complex, constrained, nonlinear, multiple objective problem. GAs are implemented using both binary and floating point representations with associated mutation and crossover ...
Could we design quantum ML algorithms that can predict ground state properties by learning from far fewer experiments than any classical ML algorithm? Perhaps this could be shown by combining ideas from adiabatic quantum computation37,38,39,40,41,42,43,44 and recent techniques for proving quantum...
Software designers, and architects in particular, tend to evaluate solutions by how elegant and optimum they are for a given problem My advice: Don’t give in to the temptation to make your design, or your implementation, perfect! Aim for “good enough” and stop when you’ve achieved it ...
FLalgorithm selectionis an important consideration in the design of efficient and effective FL systems forvehicular communications. The selection of the appropriate FL algorithm can have a significant impact on the performance and accuracy of the learning model, as well as theresource utilizationandcommu...