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...
The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In practice...
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...
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...
—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...