Zobrazeno 1 - 10
of 12 955
pro vyhledávání: '"Ansar, A"'
Large Language Models (LLMs) based on transformers achieve cutting-edge results on a variety of applications. However, their enormous size and processing requirements make deployment on devices with constrained resources extremely difficult. Among va
Externí odkaz:
http://arxiv.org/abs/2412.05225
Autor:
Calloo, Ansar, Evans, Matthew, Lockyer, Henry, Madiot, François, Pryer, Tristan, Zanetti, Luca
We introduce a novel property of bounded Voronoi tessellations that enables cycle-free mesh sweeping algorithms. We prove that a topological sort of the dual graph of any Voronoi tessellation is feasible in any flow direction and dimension, allowing
Externí odkaz:
http://arxiv.org/abs/2412.01660
While recent advancements in machine learning, such as LLMs, are revolutionizing software development and creative industries, they have had minimal impact on engineers designing mechanical parts, which remains largely a manual process. Existing appr
Externí odkaz:
http://arxiv.org/abs/2411.15279
Autor:
Mahmood, Tariq, Ahmad, Ibtasam, Ansar, Malik Muhammad Zeeshan, Darwish, Jumanah Ahmed, Sherwani, Rehan Ahmad Khan
In recent years, financial analysts have been trying to develop models to predict the movement of a stock price index. The task becomes challenging in vague economic, social, and political situations like in Pakistan. In this study, we employed effic
Externí odkaz:
http://arxiv.org/abs/2409.08297
Autor:
Dawn, Aditya, Ansar, Wazib
Environmental Sound Classification is an important problem of sound recognition and is more complicated than speech recognition problems as environmental sounds are not well structured with respect to time and frequency. Researchers have used various
Externí odkaz:
http://arxiv.org/abs/2408.13644
A language is made up of an infinite/finite number of sentences, which in turn is composed of a number of words. The Electrocardiogram (ECG) is the most popular noninvasive medical tool for studying heart function and diagnosing various irregular car
Externí odkaz:
http://arxiv.org/abs/2407.11102
Autor:
Ansar, Nadia, Ansari, Mohammad Sadique, Sharique, Mohammad, Khatoon, Aamina, Malik, Md Abdul, Siddiqui, Md Munir
There have been significant issues given the IoT, with heterogeneity of billions of devices and with a large amount of data. This paper proposed an innovative design of the Internet of Things (IoT) Environment Intrusion Detection System (or IDS) usin
Externí odkaz:
http://arxiv.org/abs/2406.12400
One of the principal objectives of Natural Language Processing (NLP) is to generate meaningful representations from text. Improving the informativeness of the representations has led to a tremendous rise in the dimensionality and the memory footprint
Externí odkaz:
http://arxiv.org/abs/2406.04438
The advent of transformers with attention mechanisms and associated pre-trained models have revolutionized the field of Natural Language Processing (NLP). However, such models are resource-intensive due to highly complex architecture. This limits the
Externí odkaz:
http://arxiv.org/abs/2406.16893
Available training data for named entity recognition (NER) often contains a significant percentage of incorrect labels for entity types and entity boundaries. Such label noise poses challenges for supervised learning and may significantly deteriorate
Externí odkaz:
http://arxiv.org/abs/2405.07609