CiteSeerX — Author Search Results — "Ioannis Tsamardinos"

A probabilistic approach to robust execution of temporal plans with uncertainty
by Ioannis Tsamardinos — 2002 — In Methods and Applications of Artificial Intelligence: Proceedings of the Second Hellenic Conference on Artificial Intelligence
…In Temporal Planning a typical assumption is that the agent controls the execution time of all events such as starting and ending actions. In real domains however, this assumption is commonly violated and certain events are beyond the direct control of the plan’s executive. Previous work on reasonin…
Cited by 6 (1 self) – Add To MetaCart

Towards Principled Feature Selection: Relevancy, Filters and Wrappers
by Ioannis Tsamardinos, Constantin Aliferis — 2003 — in Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics
…In an influencial paper Kohavi and John [7] presented a number of disadvantages of the filter approach to the feature selection problem, steering research towards algorithms adopting the wrapper approach. We show here that neither approach is inherently better and that any practical feature selectio…
Cited by 15 (7 self) – Add To MetaCart

Fast Transformation of Temporal Plans for Efficient Execution
by Ioannis Tsamardinos, Nicola Muscettola — 1998 — In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-1998
…Temporal plans permit significant flexibility in specifying the occurrence time of events. Plan execution can make good use of that flexibility. However, the advantage of execution flexibility is counterbalanced by the cost during execution of propagating the time of occurrence of events throu…
Cited by 37 (7 self) – Add To MetaCart

Causal Explorer:Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
by Constantin Aliferis, C. F. Aliferis, Ioannis Tsamardinos, Alexander Statnikov — 2003
…Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support systems and predictive modeling or mining of causal hypothesis. Increasingly they are also being recognized as a promising for…
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Reformulating Temporal Plans For Efficient Execution
by Nicola Muscettola, Paul Morris, Ioannis Tsamardinos — 1998 — In Principles of Knowledge Representation and Reasoning
…The Simple Temporal Network formalism permits significant flexibility in specifying the occurrence time of events in temporal plans. However, to retain this flexibility during execution, there is a need to propagate the actual execution times of past events so that the occurrence windows of future e…
Cited by 40 (9 self) – Add To MetaCart

Time and Sample Efficient Discovery of Markov Blankets And Direct Causal Relations
by Ioannis Tsamardinos, Constantin Aliferis, Alexander Statnikov — 2003 — Proceedings of the 9th CAN SIGKDD International Conference on Knowledge Discovery and Data Mining
…Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, for every variable T in the network a special subset (Markov Blanket) identifiable by the network is the mini- mal variabl…
Cited by 12 (4 self) – Add To MetaCart

Algorithms for Large Scale Markov Blanket Discovery
by Ioannis Tsamardinos, Constantin Aliferis, Alexander Statnikov, Er Statnikov — 2003 — In The 16th International FLAIRS Conference, St
…This paper presents a number of new algorithras for discovering the Markov Blanket of a target variable T from training data. The Markov Blanket can be used for variable selection for classification, for causal discovery, and for Bayesian Network learning. We introduce a low-order polynomial algorit…
Cited by 10 (4 self) – Add To MetaCart

Large-Scale Feature Selection Using Markov Blanket Induction For The Prediction Of Protein-Drug Binding
by Constantin Aliferis, C. F. Aliferis, Ioannis Tsamardinos, Alexander Statnikov — 2002
…this paper we empirically evaluate a recently introduced Markov blanket induction algorithm (iterative association Markov blanket - lAMB) for the purpose of large-scale feature selection in the task of finding the optimal subset among 139,351 molecular structural properties that predict binding t…
Cited by 1 (0 self) – Add To MetaCart

Algorithms for Large-Scale Local Causal Discovery And Feature Selection In the Presence of Limited Sample Or Large Local Neighborhoods
by Constantin Aliferis, C. F. Aliferis, Ioannis Tsamardinos — 2002
…Introduction When the Causal Neighbourhood of a target node T is so large relative to the available sample then one cannot obtain statistically reliable tests of independence and association metrics when conditioning on all members of the causal neighbourhood. Thus both the growing and the shrinkin…
Cited by 4 (2 self) – Add To MetaCart

Efficient Solution Techniques for Disjunctive Temporal Reasoning Problems
by Ioannis Tsamardinos, Martha E. Pollack — 2002
…Over the past few years, a new constraint-based formalism for temporal reasoning has been developed to represent and reason about Disjunctive Temporal Problems (DTPs). The class of DTPs is significantly more expressive than other problems previously studied in constraint-based temporal reasoning. In…
Cited by 30 (10 self) – Add To MetaCart

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