Sciweavers

247 search results - page 10 / 50
» On Finding Large Conjunctive Clusters
Sort
View
FLAIRS
2004
13 years 9 months ago
Clustering Spatial Data in the Presence of Obstacles
Clustering is a form of unsupervised machine learning. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing an...
Xin Wang, Howard J. Hamilton
SIAMSC
2008
182views more  SIAMSC 2008»
13 years 7 months ago
A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation
We propose a distributed algorithm for solving Euclidean metric realization problems arising from large 3D graphs, using only noisy distance information, and without any prior kno...
Pratik Biswas, Kim-Chuan Toh, Yinyu Ye
CORR
2006
Springer
178views Education» more  CORR 2006»
13 years 7 months ago
A tool set for the quick and efficient exploration of large document collections
: We are presenting a set of multilingual text analysis tools that can help analysts in any field to explore large document collections quickly in order to determine whether the do...
Camelia Ignat, Bruno Pouliquen, Ralf Steinberger, ...
CPM
2006
Springer
140views Combinatorics» more  CPM 2006»
13 years 11 months ago
Identifying Co-referential Names Across Large Corpora
A single logical entity can be referred to by several different names over a large text corpus. We present our algorithm for finding all suchco-reference sets in a large corpus. Ou...
Levon Lloyd, Andrew Mehler, Steven Skiena
HIS
2004
13 years 9 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...