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CINQ
2004
Springer
119views Database» more  CINQ 2004»
15 years 3 months ago
How to Quickly Find a Witness
The subfield of itemset mining is essentially a collection of algorithms. Whenever a new type of constraint is discovered, a specialized algorithm is proposed to handle it. All o...
Daniel Kifer, Johannes Gehrke, Cristian Bucila, Wa...
KDD
1997
ACM
96views Data Mining» more  KDD 1997»
15 years 2 months ago
Mining Association Rules with Item Constraints
The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In practice...
Ramakrishnan Srikant, Quoc Vu, Rakesh Agrawal
COLT
2008
Springer
14 years 11 months ago
Adaptive Aggregation for Reinforcement Learning with Efficient Exploration: Deterministic Domains
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
Andrey Bernstein, Nahum Shimkin
AAAI
2010
14 years 11 months ago
Learning Causal Models of Relational Domains
Methods for discovering causal knowledge from observational data have been a persistent topic of AI research for several decades. Essentially all of this work focuses on knowledge...
Marc Maier, Brian Taylor, Huseyin Oktay, David Jen...
DMIN
2007
110views Data Mining» more  DMIN 2007»
14 years 11 months ago
Mining for Structural Anomalies in Graph-based Data
—In this paper we present graph-based approaches to mining for anomalies in domains where the anomalies consist of unexpected entity/relationship alterations that closely resembl...
William Eberle, Lawrence B. Holder