Inference algorithms for pattern-based CRFs on sequence data

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. ML Research Press2013Atlanta, GA, USA eng ICML'13 Proceedings of the 30th International Conference on International 000381149500002 283145 - 153 https://research-explorer.ista.ac.at/record/1794 Takhanov, R., & Kolmogorov, V. (2013). Inference algorithms for pattern-based CRFs on sequence data. In ICML’13 Proceedings of the 30th International Conference on International (Vol. 28, pp. 145–153). Atlanta, GA, USA: ML Research Press. R. Takhanov and V. Kolmogorov, “Inference algorithms for pattern-based CRFs on sequence data,” in ICML’13 Proceedings of the 30th International Conference on International, 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.” In ICML’13 Proceedings of the 30th International Conference on International, 28:145–53. ML Research Press, 2013. R. Takhanov, V. Kolmogorov, in:, ICML’13 Proceedings of the 30th International Conference on International, ML Research Press, 2013, pp. 145–153. Takhanov R, Kolmogorov V. Inference algorithms for pattern-based CRFs on sequence data. In: ICML’13 Proceedings of the 30th International Conference on International. Vol 28. ML Research Press; 2013:145-153. 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.” ICML’13 Proceedings of the 30th International Conference on International, vol. 28, no. 3, ML Research Press, 2013, pp. 145–53. 22722018-12-11T11:56:41Z2025-09-29T14:28:48Z