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» Bayesian Algorithms for Causal Data Mining
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APN
2007
Springer
14 years 1 months ago
ProM 4.0: Comprehensive Support for Real Process Analysis
This tool paper describes the functionality of ProM. Version 4.0 of ProM has been released at the end of 2006 and this version reflects recent achievements in process mining. Proc...
Wil M. P. van der Aalst, Boudewijn F. van Dongen, ...
WWW
2006
ACM
14 years 8 months ago
Probabilistic models for discovering e-communities
The increasing amount of communication between individuals in e-formats (e.g. email, Instant messaging and the Web) has motivated computational research in social network analysis...
Ding Zhou, Eren Manavoglu, Jia Li, C. Lee Giles, H...
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
13 years 11 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 5 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
SDM
2010
SIAM
182views Data Mining» more  SDM 2010»
13 years 8 months ago
HCDF: A Hybrid Community Discovery Framework
We introduce a novel Bayesian framework for hybrid community discovery in graphs. Our framework, HCDF (short for Hybrid Community Discovery Framework), can effectively incorporate...
Keith Henderson, Tina Eliassi-Rad, Spiros Papadimi...