no code implementations • 4 Apr 2023 • Zahra Sadeghi, Roohallah Alizadehsani, Mehmet Akif Cifci, Samina Kausar, Rizwan Rehman, Priyakshi Mahanta, Pranjal Kumar Bora, Ammar Almasri, Rami S. Alkhawaldeh, Sadiq Hussain, Bilal Alatas, Afshin Shoeibi, Hossein Moosaei, Milan Hladik, Saeid Nahavandi, Panos M. Pardalos
This paper presents a systematic review of XAI aspects and challenges in the healthcare domain.
no code implementations • 21 Sep 2021 • Seonho Park, Maciej Rysz, Kathleen M. Dipple, Panos M. Pardalos
Deep learning-based image retrieval has been emphasized in computer vision.
no code implementations • 14 Apr 2021 • Seonho Park, Panos M. Pardalos
Estimating the data density is one of the challenging problems in deep learning.
1 code implementation • 5 May 2020 • Seonho Park, George Adosoglou, Panos M. Pardalos
Building a scalable machine learning system for unsupervised anomaly detection via representation learning is highly desirable.
1 code implementation • 27 Jun 2019 • Seonho Park, Seung Hyun Jung, Panos M. Pardalos
In this paper, we suggest an algorithm combining negative curvature with the adaptive cubic regularized Newton method to update even at unsuccessful iterations.
no code implementations • 26 Apr 2018 • Anton Kocheturov, Petar Momcilovic, Azra Bihorac, Panos M. Pardalos
We develop a new method called the Fast Temporal Pattern Mining with Extended Vertical Lists.
no code implementations • 19 Feb 2018 • Patrick Emami, Panos M. Pardalos, Lily Elefteriadou, Sanjay Ranka
Data association is a key step within the multi-object tracking pipeline that is notoriously challenging due to its combinatorial nature.
no code implementations • 9 Jan 2017 • Valery A. Kalyagin, Alexander P. Koldanov, Petr A. Koldanov, Panos M. Pardalos
However, in graphical model selection it is also important to take into account error rates for incorrect edge exclusion (Type II error).