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pro vyhledávání: '"Belaid, Mohamed"'
Pairwise difference learning (PDL) has recently been introduced as a new meta-learning technique for regression. Instead of learning a mapping from instances to outcomes in the standard way, the key idea is to learn a function that takes two instance
Externí odkaz:
http://arxiv.org/abs/2406.20031
Autor:
Belaid, Mohamed-Bachir, Sharma, Jivitesh, Jiao, Lei, Granmo, Ole-Christoffer, Andersen, Per-Arne, Yazidi, Anis
Tsetlin Machines (TMs) have garnered increasing interest for their ability to learn concepts via propositional formulas and their proven efficiency across various application domains. Despite this, the convergence proof for the TMs, particularly for
Externí odkaz:
http://arxiv.org/abs/2310.02005
With the rapid growth of data availability and usage, quantifying the added value of each training data point has become a crucial process in the field of artificial intelligence. The Shapley values have been recognized as an effective method for dat
Externí odkaz:
http://arxiv.org/abs/2304.01224
In recent years, Explainable AI (xAI) attracted a lot of attention as various countries turned explanations into a legal right. xAI allows for improving models beyond the accuracy metric by, e.g., debugging the learned pattern and demystifying the AI
Externí odkaz:
http://arxiv.org/abs/2207.14160
In most optimization problems, users have a clear understanding of the function to optimize (e.g., minimize the makespan for scheduling problems). However, the constraints may be difficult to state and their modelling often requires expertise in Cons
Externí odkaz:
http://arxiv.org/abs/2111.11871
Autor:
Belaid, Mohamed-Bachir, Lazaar, Nadjib
The problem of discovering frequent itemsets including rare ones has received a great deal of attention. The mining process needs to be flexible enough to extract frequent and rare regularities at once. On the other hand, it has recently been shown t
Externí odkaz:
http://arxiv.org/abs/2109.07844
Publikováno v:
In Case Studies in Thermal Engineering July 2024 59
Autor:
Afif, Hana1 (AUTHOR) hana.afif@univ-annaba.dz, Belaid, Mohamed Mouloud1 (AUTHOR), Radu, Valentin2 (AUTHOR)
Publikováno v:
Valahian Journal of Economic Studies. Jun2024, Vol. 15 Issue 1, p15-26. 12p.
Itemset mining is one of the most studied tasks in knowledge discovery. In this paper we analyze the computational complexity of three central itemset mining problems. We prove that mining confident rules with a given item in the head is NP-hard. We
Externí odkaz:
http://arxiv.org/abs/2012.02619
Autor:
Belaid, Mohamed Karim
From object segmentation to word vector representations, Scene Graph Generation (SGG) became a complex task built upon numerous research results. In this paper, we focus on the last module of this model: the fusion function. The role of this latter i
Externí odkaz:
http://arxiv.org/abs/2011.04779