no code implementations • 4 Dec 2023 • Muhammad Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos C. Machado, Adam White
In this paper we investigate the use of reinforcement-learning based prediction approaches for a real drinking-water treatment plant.
no code implementations • 30 Mar 2022 • Han Wang, Erfan Miahi, Martha White, Marlos C. Machado, Zaheer Abbas, Raksha Kumaraswamy, Vincent Liu, Adam White
In this paper we investigate the properties of representations learned by deep reinforcement learning systems.
1 code implementation • 21 Nov 2021 • Amir Abbasi, Erfan Miahi, Seyed Abolghasem Mirroshandel
Moreover, this is the first time that the concept of multi-task learning has been introduced to the field of Sperm Morphology Analysis (SMA).
no code implementations • 29 Sep 2021 • Erfan Miahi, Revan MacQueen, Alex Ayoub, Abbas Masoumzadeh, Martha White
Soft-greedy operators, namely $\varepsilon$-greedy and softmax, remain a common choice to induce a basic level of exploration for action-value methods in reinforcement learning.
1 code implementation • 3 Dec 2020 • Mojtaba Shakeri, Erfan Miahi, Abhishek Gupta, Yew-Soon Ong
Under such settings, existing transfer evolutionary optimization frameworks grapple with simultaneously satisfying two important quality attributes, namely (1) scalability against a growing number of source tasks and (2) online learning agility against sparsity of relevant sources to the target task of interest.
no code implementations • 20 Sep 2019 • Erfan Miahi, Seyed Abolghasem Mirroshandel, Alexis Nasr
Every individual of the genetic algorithm is a convolutional neural network trained to predict morphological deformities in different segments of human sperm (head, vacuole, and acrosome), and its fitness is calculated by a novel proposed method named GeNAS-WF especially designed for noisy, low resolution, and imbalanced datasets.