no code implementations • 8 Jan 2024 • Shourav B. Rabbani, Ivan V. Medri, Manar D. Samad
To the best of our knowledge, this is the first benchmarking paper with statistical analyses of attention and contrastive learning performances on a diverse selection of tabular data sets against traditional deep and machine learning baselines to facilitate further advances in this field.
no code implementations • 11 Jun 2023 • Shourav B. Rabbani, Manar D. Samad
We investigate our hypothesis using several GNNs and state-of-the-art (SOTA) deep attention models to learn the between-sample relationship on ten tabular data sets by comparing them to traditional machine learning methods.
no code implementations • 10 Feb 2023 • Maksims Kazijevs, Manar D. Samad
The imputation of missing values in multivariate time series (MTS) data is critical in ensuring data quality and producing reliable data-driven predictive models.
no code implementations • 2 Jan 2023 • Manar D. Samad, Sakib Abrar, Mohammad Bataineh
In this paper, we address the challenges of learning tabular data in contrast to image data and present a novel Gaussian Cluster Embedding in Autoencoder Latent Space (G-CEALS) algorithm by replacing t-distributions with multivariate Gaussian clusters.
no code implementations • 28 Dec 2022 • Sakib Abrar, Ali Sekmen, Manar D. Samad
Eight clustering and state-of-the-art embedding clustering methods proposed for image data sets are tested on seven tabular data sets.
no code implementations • 18 Sep 2022 • Megan A. Witherow, Manar D. Samad, Norou Diawara, Haim Y. Bar, Khan M. Iftekharuddin
We propose domain adaptation to concurrently align distributions of adult and child expressions in a shared latent space for robust classification of either domain.
no code implementations • 24 Aug 2021 • Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry
Besides, existing intrusion detection systems (IDSs) often propose to tackle a specific type of attack, which may leave a system vulnerable to numerous other types of attacks.
no code implementations • 25 Jul 2020 • Manar D. Samad, Nalin D. Khounviengxay, Megan A. Witherow
However, text processing steps are often performed using off-the-shelf routines and pre-built word dictionaries without optimizing for domain, application, and context.
no code implementations • 16 Aug 2019 • Mahbubul Alam, Manar D. Samad, Lasitha Vidyaratne, Alexander Glandon, Khan M. Iftekharuddin
This survey presents a review of state-of-the-art deep neural network architectures, algorithms, and systems in vision and speech applications.