WeproposeanewapproachtoEMlearning of PCFGs. We completely separate the process of EM learning from that of parsing, andfor theformer, weintroduce a new EM algorithm called the gra...
The scalability problem in data mining involves the development of methods for handling large databases with limited computational resources. In this paper, we present a two-phase...
We give a new algorithm for the genotype phasing problem. Our solution is based on a hidden Markov model for haplotypes. The model has a uniform structure, unlike most solutions pr...
Pasi Rastas, Mikko Koivisto, Heikki Mannila, Esko ...
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...
EM algorithm is an important unsupervised clustering algorithm, but the algorithm has several limitations. In this paper, we propose a fast EM algorithm (FEMA) to address the limi...
Abstract. In this paper, we present a novel algorithm to detect homogeneous color regions in images. We show its performance by applying it to skin detection. In contrast to previo...
— Decision directed channel tracking (DDCT) at high fade rates in OFDM based systems is addressed in this paper. Existing DDCT algorithms like the expectation-maximization (EM) a...
— We propose an expectation-maximization (EM) technique for locating multiple transmitters based on power levels observed by a set of arbitrarily-placed receivers. Multiple trans...
Abstract—This paper proposes a new iterative channel estimation algorithm for known symbol padding (KSP) Orthogonal Frequency Division Multiplexing (OFDM) based on the Expectatio...
This paper presents a new enhanced text extraction algorithm from degraded document images on the basis of the probabilistic models. The observed document image is considered as a...