Margin-infused relaxed algorithm
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Margin Infused Relaxed Algorithm (MIRA)[1] is a machine learning algorithm, an online algorithm for multiclass classification problems.
It is designed to learn a set of parameters (vector or matrix) by processing all the given training examples one-by-one and updating the parameters after each iteration.
The flow of the algorithm[2][3] looks as follows:
Algorithm MIRA Input: Training examples Output: Set of parameters
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References
- ^ Crammer, K., Singer, Y. (2003): Ultraconservative Online Algorithms for Multiclass Problems. In: Journal of Machine Learning Research 3, 951-991.
- ^ Wanatabe, T. et al (2007): Online Large Margin Training for Statistical Machine Translation. In: Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 764–773.
- ^ Bohnet, B. (2009): Efficient Parsing of Syntactic and Semantic Dependency Structures. Proceedings of Conference on Natural Language Learning (CoNLL), Boulder, 67-72.