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» Spectral Clustering and Embedding with Hidden Markov Models
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ICML
2007
IEEE
14 years 8 months ago
Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
Kai Ni, Lawrence Carin, David B. Dunson
ICIP
2006
IEEE
14 years 9 months ago
Detection of Drivable Corridors for Off-Road Autonomous Navigation
This paper describes a hierarchical Bayesian network used for segmenting desert images and detecting off road drivable corridors for autonomous navigation. Unlike the embedded hid...
Ara V. Nefian, Gary R. Bradski
NIPS
2004
13 years 9 months ago
Hierarchical Eigensolver for Transition Matrices in Spectral Methods
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Chakra Chennubhotla, Allan D. Jepson
NETWORKING
2004
13 years 9 months ago
Modeling the Short-Term Unfairness of IEEE 802.11 in Presence of Hidden Terminals
: IEEE 802.11 exhibits both short-term and long-term unfairness [15]. The short-term fairness automatically gives rise to long-term fairness, but not vice versa [11]. When we thoro...
Zhifei Li, Sukumar Nandi, Anil K. Gupta
ICDAR
2003
IEEE
14 years 25 days ago
A Low-Cost Parallel K-Means VQ Algorithm Using Cluster Computing
In this paper we propose a parallel approach for the Kmeans Vector Quantization (VQ) algorithm used in a twostage Hidden Markov Model (HMM)-based system for recognizing handwritte...
Alceu de Souza Britto Jr., Paulo Sergio Lopes de S...