Search Results - "Lonlac, Jerry"

A methodological and theoretical framework for implementing explainable artificial intelligence (XAI) in business applications by Tchuente, Dieudonné, Lonlac, Jerry, Kamsu-Foguem, Bernard

“…Artificial Intelligence (AI) is becoming fundamental in almost all activity sectors in our society. However, most of the modern AI techniques (e.g., Machine…”
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GRAPGT: GRAdual patterns with gradualness threshold by Chirmeni Boujike, Michael, Lonlac, Jerry, Tsopze, Norbert, Mephu Nguifo, Engelbert, Pauline Fotso, Laure

“…The traditional algorithms that extract the gradual patterns often face the problem of managing the quantity of mined patterns, and in many applications, the…”
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Mining Gradual Itemsets Using Sequential Pattern Mining by Jabbour, Said, Lonlac, Jerry, Sais, Lakhdar

“…Gradual itemsets model complex attributes covariation of the form "The more or less is A, the more or less is B". Recently, such kind of itemsets have received…”
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Extracting Frequent (Closed) Seasonal Gradual Patterns Using Closed Itemset Mining by Come, Aymeric, Lonlac, Jerry

“…In this paper, we address the issue of mining seasonal gradual patterns, which consists in identifying attribute co-variations in the form "when X…”
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A Constraint-based Approach for Enumerating Gradual Itemsets by Hidouri, Amel, Jabbour, Said, Lonlac, Jerry, Raddaoui, Badran

“…Gradual itemsets model complex attributes covariations of the form the more or less is A, the more or less is B. Recently, such kind of itemsets has received…”
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Extracting Seasonal Gradual Patterns from Temporal Sequence Data Using Periodic Patterns Mining by Lonlac, Jerry, Doniec, Arnaud, Lujak, Marin, Lecoeuche, Stephane

“…Mining frequent episodes aims at recovering sequential patterns from temporal data sequences, which can then be used to predict the occurrence of related…”
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Towards Learned Clauses Database Reduction Strategies Based on Dominance Relationship by Lonlac, Jerry, Nguifo, Engelbert Mephu

“…Clause Learning is one of the most important components of a conflict driven clause learning (CDCL) SAT solver that is effective on industrial instances. Since…”
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Discovering Frequent Gradual Itemsets with Imprecise Data by Boujike, Michaël Chirmeni, Lonlac, Jerry, Tsopze, Norbert, Nguifo, Engelbert Mephu

“…The gradual patterns that model the complex co-variations of attributes of the form "The more/less X, The more/less Y" play a crucial role in many real world…”
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Extending modern SAT solvers for models enumeration by Jabbour, Said, Lonlac, Jerry, Sais, Lakhdar, Salhi, Yakoub

“…In this paper, we address the problem of enumerating all models of a Boolean formula in conjunctive normal form (CNF). We propose an extension of Conflict…”
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Extracting Frequent Gradual Patterns Using Constraints Modeling by Lonlac, Jerry, Jabbour, Saïdd, Nguifo, Engelbert Mephu, Saïs, Lakhdar, Raddaoui, Badran

“…In this paper, we propose a constraint-based modeling approach for the problem of discovering frequent gradual patterns in a numerical dataset. This SAT-based…”
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An Approach for Extracting Frequent (Closed) Gradual Patterns Under Temporal Constraint by Lonlac, Jerry, Miras, Yannick, Beauger, Aude, Mazenod, Vincent, Peiry, Jean-Luc, Nguifo, Engelbert Mephu

“…Gradual patterns that capture the order correlations of the form "The more/less X, then the more/less Y" play an important role in many real world…”
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Diversification by Clauses Deletion Strategies in Portfolio Parallel SAT Solving by Long Guo, Jabbour, Said, Lonlac, Jerry, Sais, Lakhdar

“…Conflict based clause learning is known to be an important component in Modern SAT solving. Because of the exponential blow up of the size of learnt clauses…”
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Revisiting the Learned Clauses Database Reduction Strategies by Jabbour, Said, Lonlac, Jerry, Sais, Lakhdar, Salhi, Yakoub

“…In this paper, we revisit an important issue of CDCL-based SAT solvers, namely the learned clauses database management policies. Our motivation takes its…”
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Extending Resolution by Dynamic Substitution of Boolean Functions by Jabbour, S., Lonlac, J., Sais, L.

“…This paper presents a dynamic substitution technique of Boolean functions. It first recovers a set of Boolean functions from Boolean formula in conjunctive…”
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