Zobrazeno 1 - 10
of 341
pro vyhledávání: '"Anava, A."'
Autor:
Putri Andini, Anava Nesia Santoso, Kezia Yokbeth Wilhelmina Danomira, Martdian Ratna Sari, Noveri Maulana
Publikováno v:
Journal of Management and Business Review, Vol 20, Iss 3, Pp 502-519 (2023)
Financial fraud is among the rarest forms, resulting in the greatest organizational losses. Financial and reputational crises are examples of the costs of financial manipulation. In detecting fraud, much research has been carried out regarding the fa
Externí odkaz:
https://doaj.org/article/8acedef3f6d64572b0ff856b77b37a2b
Autor:
Anava, Oren, Levy, Kfir Y.
The weighted k-nearest neighbors algorithm is one of the most fundamental non-parametric methods in pattern recognition and machine learning. The question of setting the optimal number of neighbors as well as the optimal weights has received much att
Externí odkaz:
http://arxiv.org/abs/1701.07266
Autor:
Anava, Oren, Golan, Shahar, Golbandi, Nadav, Karnin, Zohar, Lempel, Ronny, Rokhlenko, Oleg, Somekh, Oren
It is well known that collaborative filtering (CF) based recommender systems provide better modeling of users and items associated with considerable rating history. The lack of historical ratings results in the user and the item cold-start problems.
Externí odkaz:
http://arxiv.org/abs/1406.2431
Autor:
de Santos-Sierra, Daniel, Sendiña-Nadal, Irene, Leyva, Inmaculada, Almendral, Juan A., Anava, Sarit, Ayali, Amir, Papo, David, Boccaletti, Stefano
Publikováno v:
PLoS ONE 9(1): e85828 (2014)
In vitro primary cultures of dissociated invertebrate neurons from locust ganglia are used to experimentally investigate the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elabo
Externí odkaz:
http://arxiv.org/abs/1311.0164
The framework of online learning with memory naturally captures learning problems with temporal constraints, and was previously studied for the experts setting. In this work we extend the notion of learning with memory to the general Online Convex Op
Externí odkaz:
http://arxiv.org/abs/1302.6937
In this paper we address the problem of predicting a time series using the ARMA (autoregressive moving average) model, under minimal assumptions on the noise terms. Using regret minimization techniques, we develop effective online learning algorithms
Externí odkaz:
http://arxiv.org/abs/1302.6927
Publikováno v:
In Complementary Therapies in Medicine December 2018 41:99-104
Akademický článek
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Autor:
Izadi, Zhila, Hajizadeh-Saffar, Ensiyeh, Hadjati, Jamshid, Habibi-Anbouhi, Mahdi, Ghanian, Mohammad Hossein, Sadeghi-Abandansari, Hamid, Ashtiani, Mohammad Kazemi, Samsonchi, Zakieh, Raoufi, Mohammad, Moazenchi, Maedeh, Izadi, Mahmoud, Nejad, Anava sadat Sadr Hashemi, Namdari, Haideh, Tahamtani, Yaser, Ostad, Seyed Nasser, Akbari-Javar, Hamid, Baharvand, Hossein
Publikováno v:
In Biomaterials November 2018 182:191-201
Publikováno v:
The Condor, 2001 May 01. 103(2), 376-380.
Externí odkaz:
https://www.jstor.org/stable/1370385