The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
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693-723
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Cites
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
(2021) · A First Course in Statistical Programming with R · doi:10.1017/9781108993456.011 · Cited by 13,724
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
Lafferty, J., McCallum, A., & Pereira, F. C. N. (2001) · ScholarlyCommons (University of Pennsylvania) · Cited by 12,935
Self-citationWolpert, D. H. (1992) · Neural Networks · doi:10.1016/s0893-6080(05)80023-1 · Cited by 7,951
Building a Large Annotated Corpus of English: The Penn Treebank
Marcus, M. (1993) · doi:10.21236/ada273556 · Cited by 7,405
Training Products of Experts by Minimizing Contrastive Divergence
Hinton, G. E. (2002) · Neural Computation · doi:10.1162/089976602760128018 · Cited by 4,879
A maximum entropy approach to natural language processing
Berger, A. L., Pietra, V. J. D., & Pietra, S. A. D. (1996) · doi:10.5555/234285.234289 · Cited by 3,065
Dynamic bayesian networks: representation, inference and learning
Murphy, K. P., & Russell, S. (2002) · Cited by 2,575
Collins, M. (2002) · Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02 · doi:10.3115/1118693.1118694 · Cited by 1,862
Constructing Free-Energy Approximations and Generalized Belief Propagation Algorithms
Yedidia, J. S., Freeman, W. T., & Weiss, Y. (2005) · IEEE Transactions on Information Theory · doi:10.1109/tit.2005.850085 · Cited by 1,617
Cited by
Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation
Phillips, S. J., & Dudík, M. (2008) · Ecography · doi:10.1111/j.0906-7590.2008.5203.x · Cited by 5,890
A unified architecture for natural language processing: deep neural networks with multitask learning
Collobert, R., & Weston, J. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08 · doi:10.1145/1390156.1390177 · Cited by 5,058
Natural Language Processing (almost) from Scratch
Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., & Kuksa, P. P. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1103.0398 · Cited by 4,962
Time-series clustering – A decade review
Aghabozorgi, S., Seyed Shirkhorshidi, A., & Ying Wah, T. (2015) · Information Systems · doi:10.1016/j.is.2015.04.007 · Cited by 1,826
Fourcade, Y., Engler, J. O., Rödder, D., & Secondi, J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0097122 · Cited by 1,098
Metadata
- Authors
- Sutton, C., Rohanimanesh, K., & McCallum, A.
- Venue
- Twenty-first international conference on Machine learning - ICML '04
- Publisher
- ACM Press
- Published
- 2004
- Volume
- 8
- Issue
- 25
- Pages
- 99
- OpenAlex
- W2152463966
- Cited by
- 284
- References
- 53
- FWCI
- 28.37
- Type
- journal article
- Language
- en
- Open access
- green
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- Sutton, C., Rohanimanesh, K., & McCallum, A. (2004). Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data. Twenty-first international conference on Machine learning - ICML '04. https://doi.org/10.1145/1015330.1015422
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
