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This is a list of algorithm general topics. Analysis of algorithms; Ant colony algorithm; Approximation algorithm; Best and worst cases; Big O notation; Combinatorial search; Competitive analysis; Computability theory; Computational complexity theory; Embarrassingly parallel problem; Emergent algorithm; Evolutionary algorithm; Fast Fourier ...
In a 1966 Ph.D. thesis, ... visual programming tool for data mining, statistical data analysis, and machine learning. ... Library for C++, mainly aimed at hardware ...
High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce ...
A Tsetlin machine is a form of learning automaton collective for learning patterns using propositional logic. Ole-Christoffer Granmo created [ 1 ] and gave the method its name after Michael Lvovitch Tsetlin , who invented the Tsetlin automaton [ 2 ] and worked on Tsetlin automata collectives and games. [ 3 ]
Dlib is a general purpose cross-platform software library written in the programming language C++.Its design is heavily influenced by ideas from design by contract and component-based software engineering.
Pioneering machine learning research is conducted using simple algorithms. 1960s: Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s 'AI winter' caused by pessimism about machine learning effectiveness. 1980s: Rediscovery of backpropagation causes a resurgence in machine learning research. 1990s
The parallel computation thesis is not a rigorous formal statement, as it does not clearly define what constitutes an acceptable parallel model. A parallel machine must be sufficiently powerful to emulate the sequential machine in time polynomially related to the sequential space; compare Turing machine , non-deterministic Turing machine , and ...
Soar [1] is a cognitive architecture, [2] originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University.. The goal of the Soar project is to develop the fixed computational building blocks necessary for general intelligent agents – agents that can perform a wide range of tasks and encode, use, and learn all types of knowledge to realize the full range of ...