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PKDD
2009
Springer
102views Data Mining» more  PKDD 2009»
15 years 8 months ago
Relevance Grounding for Planning in Relational Domains
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Tobias Lang, Marc Toussaint
81
Voted
ICDM
2008
IEEE
106views Data Mining» more  ICDM 2008»
15 years 8 months ago
Boosting Relational Sequence Alignments
The task of aligning sequences arises in many applications. Classical dynamic programming approaches require the explicit state enumeration in the reward model. This is often impr...
Andreas Karwath, Kristian Kersting, Niels Landwehr
ICDM
2005
IEEE
168views Data Mining» more  ICDM 2005»
15 years 7 months ago
A Scalable Collaborative Filtering Framework Based on Co-Clustering
Collaborative filtering-based recommender systems, which automatically predict preferred products of a user using known preferences of other users, have become extremely popular ...
Thomas George, Srujana Merugu
SDM
2010
SIAM
191views Data Mining» more  SDM 2010»
15 years 3 months ago
Active Ordering of Interactive Prediction Tasks
Many applications involve a set of prediction tasks that must be accomplished sequentially through user interaction. If the tasks are interdependent, the order in which they are p...
Abhimanyu Lad, Yiming Yang
ICDM
2010
IEEE
142views Data Mining» more  ICDM 2010»
14 years 12 months ago
Causal Discovery from Streaming Features
In this paper, we study a new research problem of causal discovery from streaming features. A unique characteristic of streaming features is that not all features can be available ...
Kui Yu, Xindong Wu, Hao Wang, Wei Ding