Zobrazeno 1 - 10
of 7 565
pro vyhledávání: '"A. Tabar"'
Data-driven organizations around the world routinely use forecasting methods to improve their planning and decision-making capabilities. Although much research exists on the harms resulting from traditional machine learning applications, little has s
Externí odkaz:
http://arxiv.org/abs/2411.16531
Autor:
Farahmand-Tabar, Salar
Publikováno v:
In: Kulkarni, A.J., Gandomi, A.H. (eds) Handbook of Formal Optimization. Springer, 2024
Metaheuristics are stochastic optimization algorithms that mimic natural processes to find optimal solutions to complex problems. The success of metaheuristics largely depends on the ability to effectively explore and exploit the search space. Memory
Externí odkaz:
http://arxiv.org/abs/2411.15151
Autor:
Farahmand-Tabar, Salar, Ashtari, Payam
Publikováno v:
(2023) In: Kulkarni, A.J., Gandomi, A.H. (eds) Handbook of Formal Optimization. Springer
An improved bilinear fuzzy genetic algorithm (BFGA) is introduced in this chapter for the design optimization of steel structures with semi-rigid connections. Semi-rigid connections provide a compromise between the stiffness of fully rigid connection
Externí odkaz:
http://arxiv.org/abs/2411.05865
Autor:
Farahmand-Tabar, Salar, Shirgir, Sina
Publikováno v:
In: Kulkarni, A.J., Gandomi, A.H. (eds) Handbook of Formal Optimization. Springer, 2024
Opposition-based learning (OBL) is an effective approach to improve the performance of metaheuristic optimization algorithms, which are commonly used for solving complex engineering problems. This chapter provides a comprehensive review of the litera
Externí odkaz:
http://arxiv.org/abs/2411.05864
Autor:
Ghaznavi, Mahdi, Asadollahzadeh, Hesam, Noohdani, Fahimeh Hosseini, Tabar, Soroush Vafaie, Hasani, Hosein, Alvanagh, Taha Akbari, Rohban, Mohammad Hossein, Baghshah, Mahdieh Soleymani
Classifiers trained with Empirical Risk Minimization (ERM) tend to rely on attributes that have high spurious correlation with the target. This can degrade the performance on underrepresented (or 'minority') groups that lack these attributes, posing
Externí odkaz:
http://arxiv.org/abs/2410.05345
Autor:
Haji, Fatemeh, Bethany, Mazal, Tabar, Maryam, Chiang, Jason, Rios, Anthony, Najafirad, Peyman
Multi-agent strategies have emerged as a promising approach to enhance the reasoning abilities of Large Language Models (LLMs) by assigning specialized roles in the problem-solving process. Concurrently, Tree of Thoughts (ToT) methods have shown pote
Externí odkaz:
http://arxiv.org/abs/2409.11527
There is a large literature on the similarities and differences between biological neural circuits and deep artificial neural networks (DNNs). However, modern training of DNNs relies on several engineering tricks such as data batching, normalization,
Externí odkaz:
http://arxiv.org/abs/2408.08408
Over the past decade, there has been a severe staffing shortage in mental healthcare, exacerbated by increased demand for mental health services due to COVID-19. This demand is projected to increase over the next decade or so, necessitating proactive
Externí odkaz:
http://arxiv.org/abs/2406.17463
With growing applications of Machine Learning (ML) techniques in the real world, it is highly important to ensure that these models work in an equitable manner. One main step in ensuring fairness is to effectively measure fairness, and to this end, v
Externí odkaz:
http://arxiv.org/abs/2406.13681
Detecting faults in steel plates is crucial for ensuring the safety and reliability of the structures and industrial equipment. Early detection of faults can prevent further damage and costly repairs. This chapter aims at diagnosing and predicting th
Externí odkaz:
http://arxiv.org/abs/2405.00006