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INTERSPEECH
2010
13 years 2 months ago
Extractive summarization using a latent variable model
Extractive multi-document summarization is the task of choosing sentences from a set of documents to compose a summary text in response to a user query. We propose a generative ap...
Asli Çelikyilmaz, Dilek Hakkani-Tür
IPPS
2007
IEEE
14 years 1 months ago
A Model-Driven Approach to Job/Task Composition in Cluster Computing
In the general area of high-performance computing, object-oriented methods have gone largely unnoticed. In contrast, the Computational Neighborhood (CN), a framework for parallel ...
Neeraj Mehta, Yogesh Kanitkar, Konstantin Läu...
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
14 years 7 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
NIPS
2004
13 years 8 months ago
A Probabilistic Model for Online Document Clustering with Application to Novelty Detection
In this paper we propose a probabilistic model for online document clustering. We use non-parametric Dirichlet process prior to model the growing number of clusters, and use a pri...
Jian Zhang 0003, Zoubin Ghahramani, Yiming Yang
IJCM
2007
205views more  IJCM 2007»
13 years 7 months ago
BTF modelling using BRDF texels
The highest fidelity representations of realistic real-world materials currently used comprise Bidirectional Texture Functions (BTF). The BTF is a six dimensional function dependi...
Jirí Filip, Michal Haindl