-
generally divided into two subfields:
discrete optimization and
continuous optimization.
Optimization problems arise in all
quantitative disciplines from...
-
Continuous optimization is a
branch of
optimization in
applied mathematics. As
opposed to
discrete optimization, the
variables used in the
objective function...
- In
computer science,
program optimization, code
optimization, or
software optimization is the
process of
modifying a
software system to make some aspect...
- In
machine learning,
hyperparameter optimization or
tuning is the
problem of
choosing a set of
optimal hyperparameters for a
learning algorithm. A hyperparameter...
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Combinatorial optimization is a
subfield of
mathematical optimization that
consists of
finding an
optimal object from a
finite set of objects,
where the...
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Convex optimization is a
subfield of
mathematical optimization that
studies the
problem of
minimizing convex functions over
convex sets (or, equivalently...
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Shape optimization is part of the
field of
optimal control theory. The
typical problem is to find the
shape which is
optimal in that it
minimizes a certain...
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Bayesian optimization is a
sequential design strategy for
global optimization of black-box functions, that does not ****ume any
functional forms. It is...
- Multi-objective
optimization or
Pareto optimization (also
known as multi-objective programming,
vector optimization,
multicriteria optimization, or multiattribute...
-
Proximal policy optimization (PPO) is a
reinforcement learning (RL)
algorithm for
training an
intelligent agent. Specifically, it is a
policy gradient...
