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ICML
1995
IEEE
14 years 9 months ago
Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network
Understanding high-dimensional real world data usually requires learning the structure of the data space. The structure maycontain high-dimensional clusters that are related in co...
Justine Blackmore, Risto Miikkulainen
EDBT
2012
ACM
306views Database» more  EDBT 2012»
11 years 10 months ago
Clydesdale: structured data processing on MapReduce
MapReduce has emerged as a promising architecture for large scale data analytics on commodity clusters. The rapid adoption of Hive, a SQL-like data processing language on Hadoop (...
Tim Kaldewey, Eugene J. Shekita, Sandeep Tata
SIGMOD
2012
ACM
288views Database» more  SIGMOD 2012»
11 years 10 months ago
Exploiting MapReduce-based similarity joins
Cloud enabled systems have become a crucial component to efficiently process and analyze massive amounts of data. One of the key data processing and analysis operations is the Sim...
Yasin N. Silva, Jason M. Reed
LKR
2008
13 years 9 months ago
Identification of MCMC Samples for Clustering
Abstract. For clustering problems, many studies use just MAP assignments to show clustering results instead of using whole samples from a MCMC sampler. This is because it is not st...
Kenichi Kurihara, Tsuyoshi Murata, Taisuke Sato
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
14 years 2 months ago
Incremental Spectral Clustering and Its Application To Topological Mapping
Abstract— This paper presents a novel use of spectral clustering algorithms to support cases where the entries in the affinity matrix are costly to compute. The method is increm...
Christoffer Valgren, Tom Duckett, Achim J. Lilient...