conference paper
Inference algorithms for pattern-based CRFs on sequence data
JMLR
published
yes
Rustem
Takhanov
author 2CCAC26C-F248-11E8-B48F-1D18A9856A87
Vladimir
Kolmogorov
author 3D50B0BA-F248-11E8-B48F-1D18A9856A87
VlKo
department
ICML: International Conference on Machine Learning
We consider Conditional Random Fields (CRFs) with pattern-based potentials defined on a chain. In this model the energy of a string (labeling) x1...xn is the sum of terms over intervals [i,j] where each term is non-zero only if the substring xi...xj equals a prespecified pattern α. Such CRFs can be naturally applied to many sequence tagging problems.
We present efficient algorithms for the three standard inference tasks in a CRF, namely computing (i) the partition function, (ii) marginals, and (iii) computing the MAP. Their complexities are respectively O(nL), O(nLℓmax) and O(nLmin{|D|,log(ℓmax+1)}) where L is the combined length of input patterns, ℓmax is the maximum length of a pattern, and D is the input alphabet. This improves on the previous algorithms of (Ye et al., 2009) whose complexities are respectively O(nL|D|), O(n|Γ|L2ℓ2max) and O(nL|D|), where |Γ| is the number of input patterns.
In addition, we give an efficient algorithm for sampling. Finally, we consider the case of non-positive weights. (Komodakis & Paragios, 2009) gave an O(nL) algorithm for computing the MAP. We present a modification that has the same worst-case complexity but can beat it in the best case.
International Machine Learning Society2013Atlanta, GA, USA
eng
ICML'13 Proceedings of the 30th International Conference on International
283145 - 153
https://research-explorer.app.ist.ac.at/record/1794
R. Takhanov and V. Kolmogorov, “Inference algorithms for pattern-based CRFs on sequence data,” in <i>ICML’13 Proceedings of the 30th International Conference on International</i>, Atlanta, GA, USA, 2013, vol. 28, no. 3, pp. 145–153.
Takhanov, Rustem, and Vladimir Kolmogorov. “Inference Algorithms for Pattern-Based CRFs on Sequence Data.” <i>ICML’13 Proceedings of the 30th International Conference on International</i>, vol. 28, no. 3, International Machine Learning Society, 2013, pp. 145–53.
Takhanov R, Kolmogorov V. 2013. Inference algorithms for pattern-based CRFs on sequence data. ICML’13 Proceedings of the 30th International Conference on International. ICML: International Conference on Machine Learning, JMLR, vol. 28. 145–153.
Takhanov, Rustem, and Vladimir Kolmogorov. “Inference Algorithms for Pattern-Based CRFs on Sequence Data.” In <i>ICML’13 Proceedings of the 30th International Conference on International</i>, 28:145–53. International Machine Learning Society, 2013.
R. Takhanov, V. Kolmogorov, in:, ICML’13 Proceedings of the 30th International Conference on International, International Machine Learning Society, 2013, pp. 145–153.
Takhanov R, Kolmogorov V. Inference algorithms for pattern-based CRFs on sequence data. In: <i>ICML’13 Proceedings of the 30th International Conference on International</i>. Vol 28. International Machine Learning Society; 2013:145-153.
Takhanov, R., & Kolmogorov, V. (2013). Inference algorithms for pattern-based CRFs on sequence data. In <i>ICML’13 Proceedings of the 30th International Conference on International</i> (Vol. 28, pp. 145–153). Atlanta, GA, USA: International Machine Learning Society.
22722018-12-11T11:56:41Z2020-01-21T11:41:35Z