Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Principles of artificial intelligence
Principles of artificial intelligence
Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
New Prospects in Line Detection by Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Programming Generation of Curves on Brain Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Omnifont Open-Vocabulary OCR System for English and Arabic
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document Image Decoding Using Markov Source Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Large-vocabulary speaker-independent continuous speech recognition: the sphinx system
Large-vocabulary speaker-independent continuous speech recognition: the sphinx system
Dynamic programming algorithms for maximum likelihood decoding
Dynamic programming algorithms for maximum likelihood decoding
A trellis-based recursive maximum-likelihood decoding algorithm for binary linear block codes
IEEE Transactions on Information Theory
A Coarse-to-Fine Deformable Contour Optimization Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
The generalized A* architecture
Journal of Artificial Intelligence Research
Dual decomposition for natural language processing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts of ACL 2011
A coarse-to-fine approach to computing the k-best Viterbi paths
CPM'11 Proceedings of the 22nd annual conference on Combinatorial pattern matching
Iterative viterbi A* algorithm for k-best sequential decoding
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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We introduce an extension of dynamic programming (DP) we call 驴Coarse-to-Fine Dynamic Programming驴 (CFDP), ideally suited to DP problems with large state space. CFDP uses dynamic programming to solve a sequence of coarse approximations which are lower bounds to the original DP problem. These approximations are developed by merging states in the original graph into 驴superstates驴 in a coarser graph which uses an optimistic arc cost between superstates. The approximations are designed so that when CFDP terminates the optimal path through the original state graph has been found. CFDP leads to significant decreases in the amount of computation necessary to solve many DP problems and can, in some instances, make otherwise infeasible computations possible. CFDP generalizes to DP problems with continuous state space and we offer a convergence result for this extension. The computation of the approximations requires that we bound the arc cost over all possible arcs associated with an adjacent pair of superstates; thus the feasibility of our proposed method requires the identification of such a lower bound. We demonstrate applications of this technique to optimization of functions and boundary estimation in mine recognition.