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KDD
2005
ACM
127views Data Mining» more  KDD 2005»
16 years 4 months ago
Detection of emerging space-time clusters
We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
ICOST
2011
Springer
14 years 7 months ago
Using Association Rule Mining to Discover Temporal Relations of Daily Activities
The increasing aging population has inspired many machine learning researchers to find innovative solutions for assisted living. A problem often encountered in assisted living set...
Ehsan Nazerfard, Parisa Rashidi, Diane J. Cook
IUI
2009
ACM
15 years 10 months ago
Discovering frequent work procedures from resource connections
Intelligent desktop assistants could provide more help for users if they could learn models of the users’ workflows. However, discovering desktop workflows is difficult becau...
Jianqiang Shen, Erin Fitzhenry, Thomas G. Dietteri...
ICCS
2007
Springer
15 years 10 months ago
Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems
Assimilation of spatially- and temporally-distributed state observations into simulations of dynamical systems stemming from discretized PDEs leads to inverse problems with high-di...
Omar Bashir, Omar Ghattas, Judith Hill, Bart G. va...
ICDM
2003
IEEE
112views Data Mining» more  ICDM 2003»
15 years 9 months ago
Privacy-preserving Distributed Clustering using Generative Models
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
Srujana Merugu, Joydeep Ghosh