Zobrazeno 1 - 10
of 27 098
pro vyhledávání: '"A TANVEER"'
Autor:
Manuel, Dylan, Islam, Nafis Tanveer, Khoury, Joseph, Nunez, Ana, Bou-Harb, Elias, Najafirad, Peyman
Security experts reverse engineer (decompile) binary code to identify critical security vulnerabilities. The limited access to source code in vital systems - such as firmware, drivers, and proprietary software used in Critical Infrastructures (CI) -
Externí odkaz:
http://arxiv.org/abs/2411.04981
Autor:
Quadir, A., Tanveer, M.
One of the major difficulties in machine learning methods is categorizing datasets that are imbalanced. This problem may lead to biased models, where the training process is dominated by the majority class, resulting in inadequate representation of t
Externí odkaz:
http://arxiv.org/abs/2410.20335
In the domain of machine learning, least square twin support vector machine (LSTSVM) stands out as one of the state-of-the-art models. However, LSTSVM suffers from sensitivity to noise and outliers, overlooking the SRM principle and instability in re
Externí odkaz:
http://arxiv.org/abs/2410.17338
Alzheimer's disease (AD) is a leading neurodegenerative condition and the primary cause of dementia, characterized by progressive cognitive decline and memory loss. Its progression, marked by shrinkage in the cerebral cortex, is irreversible. Numerou
Externí odkaz:
http://arxiv.org/abs/2410.14207
Publikováno v:
27th International Conference on Pattern Recognition (ICPR), 2024
In this paper, we propose enhanced feature based granular ball twin support vector machine (EF-GBTSVM). EF-GBTSVM employs the coarse granularity of granular balls (GBs) as input rather than individual data samples. The GBs are mapped to the feature s
Externí odkaz:
http://arxiv.org/abs/2410.05786
Publikováno v:
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024
On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture ModelsTwin support vector machine (TSVM) is an emerging machine learning model with versatile applicability in classification and regression endeavors.
Externí odkaz:
http://arxiv.org/abs/2410.04774
Publikováno v:
31st International Conference on Neural Information Processing (ICONIP), 2024
Random vector functional link (RVFL), a variant of single-layer feedforward neural network (SLFN), has garnered significant attention due to its lower computational cost and robustness to overfitting. Despite its advantages, the RVFL network's relian
Externí odkaz:
http://arxiv.org/abs/2410.00510
The random vector functional link (RVFL) network is a prominent classification model with strong generalization ability. However, RVFL treats all samples uniformly, ignoring whether they are pure or noisy, and its scalability is limited due to the ne
Externí odkaz:
http://arxiv.org/abs/2409.16735
Autor:
Kashyap, Satyananda, D'Souza, Niharika S., Shi, Luyao, Wong, Ken C. L., Wang, Hongzhi, Syeda-Mahmood, Tanveer
Content-addressable memories such as Modern Hopfield Networks (MHN) have been studied as mathematical models of auto-association and storage/retrieval in the human declarative memory, yet their practical use for large-scale content storage faces chal
Externí odkaz:
http://arxiv.org/abs/2409.16408
Autor:
Sonar, Vivek Ganesh, Jan, Muhammad Tanveer, Wells, Mike, Pandya, Abhijit, Engstrom, Gabriela, Shih, Richard, Furht, Borko
Accurate body weight estimation is critical in emergency medicine for proper dosing of weight-based medications, yet direct measurement is often impractical in urgent situations. This paper presents a non-invasive method for estimating body weight by
Externí odkaz:
http://arxiv.org/abs/2410.02800