Inferring Mixtures of Markov Chains-Reference-Cited by-同舟云学术

Inferring Mixtures of Markov Chains

Published:2004 Issue: Volume: Page:186-199
ISSN:0302-9743
Container-title:Learning Theory
language:
Short-container-title:

Author:

Batu Tuğkan,Guha Sudipto,Kannan Sampath

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-27819-1_13.pdf

Reference18 articles.

1. Abe, N., Warmuth, M.: On the computational complexity of approximating distributions by probabilistic automata. Machine Learning (1992) (to appear in the special issue for COLT 1990).

2. Abiteboul, S., Vianu, V., Fordham, B., Yesha,Y.: Relational transducersfor electronic commerce. pp. 179–187 (1998)

3. Arora, S., Kannan, R.: Learning mixtures of arbitrary gaussians. In: ACM Symposium on Theory of Computing, pp. 247–257 (2001)

4. Bengio, Y., Frasconi, P.: Input-output HMM’s for sequence processing. IEEE Transactions on Neural Networks 7(5), 1231–1249 (1996)

5. Burge, C.B., Karlin, S.: Finding the genes in genomic dna. J. Mol. Bio. 268(7), 8–94 (1997)

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Memetic Algorithm for Deinterleaving Pulse Trains;Evolutionary Computation in Combinatorial Optimization;2023

2. Model based Representation and Deinterleaving of Mixed Radar Pulse Sequences with Neural Machine Translation Network;IEEE Transactions on Aerospace and Electronic Systems;2021

3. Time Series Deinterleaving of DNS Traffic;2018 IEEE Security and Privacy Workshops (SPW);2018-05

4. Learning mixtures of markov chains from aggregate data with structural constraints (extended abstract);2017 IEEE 33rd International Conference on Data Engineering (ICDE);2017-04

5. Learning Mixtures of Markov Chains from Aggregate Data with Structural Constraints;IEEE Transactions on Knowledge and Data Engineering;2016-06-01