* Address all correspondence to Peter W. Roberts, Goizueta Business School, Emory University, 1300 Clifton Road, Atlanta, GA, 30322-2710; (404) 727-8585; [email protected]. Both authors thank Joel Baum, Marc Busch, Heather Haveman, Greta Hsu, Paul Ingram, Ujwal Kayande, Atul Nerkar, Toby Stuart, Harrison White, Mark Zbaracki and Ezra Zuckerman for valuable comments that led to improve...

This paper considers the Shift-And approach to the problem of pattern matching in LZW compressed text, and gives a new algorithm that solves it. The algorithm is indeed fast when a pattern length is at most 32, or the word length. After an O(m + |Σ|) time and O(|Σ|) space preprocessing of a pattern, it scans an LZW compressed text in O(n + r) time and reports all occurrences of the pattern, whe...

We demonstrate the generalizability of the Extended BaumWelch (EBW) algorithm not only for HMM parameter estimation but for decoding as well. We show that there can exist a general function associated with the objective function under EBW that reduces to the well-known auxiliary function used in the Baum-Welch algorithm for maximum likelihood estimates. We generalize representation for the upda...

In this work we consider the problem of Hidden Markov Models (HMM) training. This problem can be considered as a global optimization problem and we focus our study on the Particle Swarm Optimization (PSO) algorithm. To take advantage of the search strategy adopted by PSO, we need to modify the HMM’s search space. Moreover, we introduce a local search technique from the field of HMMs and that is...

A standard method to obtain stochastic models for symbolic time series is to train state-emitting hidden Markov models (SE-HMMs) with the Baum-Welch algorithm. Based on observable operator models (OOMs), in the last few months a number of novel learning algorithms for similar purposes have been developed: (1,2) two versions of an ”efficiency sharpening” (ES) algorithm, which iteratively improve...

We present a polynomial-time algorithm to learn an intersection of a constant number of halfspaces in n dimensions, over the uniform distribution on an n-dimensional ball. The algorithm we present in fact can learn an intersection of an arbitrary (polynomial) number of halfspaces over this distribution, if the subspace spanned by the normal vectors to the bounding hyper-planes has constant dime...

Graph theory can be applied in course scheduling. The problem discussed this study is scheduling courses the UNUGIRI Mathematics Education Study Program using graph coloring. purpose of to prevent occurrence overlap (cross-over) preparation courses. Good a schedule that carried out by all related parties teaching and learning activities. algorithm used Welch-Powell algorithm. research was condu...

In this semitutorial paper we discuss a general message passing algorithm, which we call the generalized distributive law (GDL). The GDL is a synthesis of the work of many authors in the information theory, digital communications, signal processing, statistics, and artificial intelligence communities. It includes as special cases the Baum–Welch algorithm, the fast Fourier transform (FFT) on any...

Baum-Katz theorem asserts that the Cesàro means of i.i.d. increments distributed like X r-converge if and only if |X| is integrable. We generalize this, and we unify other results, by proving that the following equivalence holds, if and only if G is moderate: the Cesàro means G-converge if and only if G(La) is integrable for every a if and only if |X| G(|X|) is integrable. Here, La is the last ...

A data-driven approach that compensates the HMM parameters for the noisy speech recognition is proposed. Instead of assuming some statistical approximations as in the conventional methods such as the PMC, the various statistical information necessary for the HMM parameter adaptation is directly estimated by using the Baum-Welch algorithm. The proposed method has shown improved results compared ...