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T1 - Optimization Algorithms for Learning Graphical Model Structures
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UR - URN:ISBN:978-951-51-7750-6; http://hdl.handle.net/10138/336484
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A1 - Rantanen, Kari
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PB - Helsingin yliopisto
Y1 - 2021
LA - eng
AB - Graphical models are a versatile machine learning framework enabling efficient and intuitive representations of probability distributions. They can be used for performing various data analysis tasks that would not be feasible otherwise. This is made possible by constructing a graph structure which encodes the underlying dependence structure of the probability distribution. To that end, the field of structure learning develops specialized algorithms which can learn a structure that describes give...
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KW - tietojenkäsittelytiede
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