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Compared with traditional use of HMMs, the complication comes from the continuous nature of u t, whereas the efficient algorithmic machinery of the HMMs (Viterbi algorithm, forward backward algorithm, expectation-maximization (EM) algorithm) works well for discrete and typically small number of hidden states (Rabiner, 1989).
Their contribution in understanding large problems and formulating efficient algorithmic solutions is underappreciated and often unrecognized.
I study the automation of the learning mechanism and its efficient algorithmic implementation.
We have developed such an efficient algorithmic framework for genome-scale models of protein synthesis.
One of the main challenges in algorithmic mechanism design is to turn (existing) efficient algorithmic solutions into efficient truthful mechanisms.
By combining efficient algorithmic knowledge sources with a rule based control mechanism, we have produced a program demonstrably expert at the game of Rogue.
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Their performance fitted nicely with the algorithmic index of efficient algorithms using bounded memory resources and no a priori information.
Our algorithmic contributions result in efficient algorithms for the convex subcoloring problem in the parameter regime of interest: a limited amount of discord for large trees.
Our approach allows us to obtain existing algorithms as special cases of well-known optimization procedures, and also easily derive new, more efficient algorithms; it may thus serve as a foundation for further algorithmic insights.
The time-space complexity of a calculus specifies how efficient its algorithmic representation is.
As the block processing of computationally efficient DFT-domain algorithms implies large algorithmic delays, the generalized multidelay adaptive filter was developed which reduces the block size by partitioning the impulse responses [31, 32].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com