Silicon dioxide-nanoparticle nutrition mitigates salinity in gerbera by modulating ion accumulation and antioxidants

Autor: Hajizadeh Hanifeh Seyed, Asadi Mahsa, Zahedi Seyed Morteza, Hamzehpour Nikoo, Rasouli Farzad, Helvacı Murat, Alas Turgut

Publikováno v: Folia Horticulturae, Vol 33, Iss 1, Pp 91-105 (2021)

This work aimed to investigate the interaction between salt stress and the application of silicon dioxide-nanoparticles. In this study, gerbera plants grown in soilless culture were supplied with nutrient solutions with different NaCl concentrations

Externí odkaz: https://doaj.org/article/10196a25931d41b88910cb69d528611e

Model-Based Reinforcement Learning Exploiting State-Action Equivalence

Autor: Asadi, Mahsa, Talebi, Mohammad Sadegh, Bourel, Hippolyte, Maillard, Odalric-Ambrym

Leveraging an equivalence property in the state-space of a Markov Decision Process (MDP) has been investigated in several studies. This paper studies equivalence structure in the reinforcement learning (RL) setup, where transition distributions are n

Externí odkaz: http://arxiv.org/abs/1910.04077

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Identifier la structure des problèmes d'apprentissage en ligne et collaboratif

Autor: Asadi, Mahsa

Publikováno v: Artificial Intelligence [cs.AI]. Université de Lille, 2022. English. ⟨NNT : 2022ULILB031⟩
Computer Science [cs]. Lille University, 2022. English. ⟨NNT : ⟩

Nowadays it is commonplace to deal with large scale problems and should we take problem structure into account, it could assist us toward improving learning performance. In this work, we have proposed approaches that take into account the structure i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::587bafa9c92e54d2420aee6fec5d388d
https://inria.hal.science/tel-03892355v2/file/These_ASADI_Mahsa.pdf

A generic framework for efficient computation of top-k diverse results.

Autor: Islam, Md Mouinul, Asadi, Mahsa, Amer-Yahia, Sihem, Roy, Senjuti Basu

Publikováno v: VLDB Journal International Journal on Very Large Data Bases; Jul2023, Vol. 32 Issue 4, p737-761, 25p