Add to ORKGAbstract. In engineering application heuristics are widely used for dis-crete optimization tasks. We report two cases (in Dense Wavelength Divi-sion Multiplexing and High Level Synthesis), where a recent \intelligent" heuristic (STAGE) performs excellently by learning a value-function of the states. We have found that if a global structure of local minima is found by the function approximator then search time may not have to scale with the dimension of the problem in the exponent, but it may become a polynomial function of the dimension.
This paper proposes and investigates a novel way of combining machine learning and heuristic search ...
Solutions to non-linear requirements engineering problems may be “brittle”; i.e. small changes may d...
To represent and learn a value function, one needs a set of features that facilitates the process by...
There exists many applications with so-called costly problems, which means that the objective functi...
One of the main objectives of science and engineering is to predict the future state of the world --...
International audienceThe optimization of high dimensional functions is a key issue in engineering p...
A value approximation-based global search algorithm is suggested to solve resource-constrained alloc...
Classical heuristic search algorithms find the solution cost of a problem while finding the path fro...
Most electronic devices we are familiar with, such as cell phones and computers, are small and requi...
Jabbari Arfaee, Zilles, and Holte presented the bootstrap learning system, a system that learns stro...
Most electronic devices we are familiar with, such as cell phones and computers, are small and requi...
In many optimization problems, the structure of solutions reflects complex relationships between the...
We present an introduction to some aspects of digital signal processing and time series analysis whi...
Heuristic search algorithms are designed to return an optimal path from a start state to a goal stat...
This paper describes algorithms that learn to improve search performance on large-scale optimization...
This paper proposes and investigates a novel way of combining machine learning and heuristic search ...
Solutions to non-linear requirements engineering problems may be “brittle”; i.e. small changes may d...
To represent and learn a value function, one needs a set of features that facilitates the process by...
There exists many applications with so-called costly problems, which means that the objective functi...
One of the main objectives of science and engineering is to predict the future state of the world --...
International audienceThe optimization of high dimensional functions is a key issue in engineering p...
A value approximation-based global search algorithm is suggested to solve resource-constrained alloc...
Classical heuristic search algorithms find the solution cost of a problem while finding the path fro...
Most electronic devices we are familiar with, such as cell phones and computers, are small and requi...
Jabbari Arfaee, Zilles, and Holte presented the bootstrap learning system, a system that learns stro...
Most electronic devices we are familiar with, such as cell phones and computers, are small and requi...
In many optimization problems, the structure of solutions reflects complex relationships between the...
We present an introduction to some aspects of digital signal processing and time series analysis whi...
Heuristic search algorithms are designed to return an optimal path from a start state to a goal stat...
This paper describes algorithms that learn to improve search performance on large-scale optimization...
This paper proposes and investigates a novel way of combining machine learning and heuristic search ...
Solutions to non-linear requirements engineering problems may be “brittle”; i.e. small changes may d...
To represent and learn a value function, one needs a set of features that facilitates the process by...