Zobrazeno 1 - 10
of 64 923
pro vyhledávání: '"A HAMEED"'
Reuse distance analysis is a widely recognized method for application characterization that illustrates cache locality. Although there are various techniques to calculate the reuse profile from dynamic memory traces, it is both time and space-consumi
Externí odkaz:
http://arxiv.org/abs/2411.13854
Autor:
Grosnit, Antoine, Maraval, Alexandre, Doran, James, Paolo, Giuseppe, Thomas, Albert, Beevi, Refinath Shahul Hameed Nabeezath, Gonzalez, Jonas, Khandelwal, Khyati, Iacobacci, Ignacio, Benechehab, Abdelhakim, Cherkaoui, Hamza, El-Hili, Youssef Attia, Shao, Kun, Hao, Jianye, Yao, Jun, Kegl, Balazs, Bou-Ammar, Haitham, Wang, Jun
We introduce Agent K v1.0, an end-to-end autonomous data science agent designed to automate, optimise, and generalise across diverse data science tasks. Fully automated, Agent K v1.0 manages the entire data science life cycle by learning from experie
Externí odkaz:
http://arxiv.org/abs/2411.03562
Fine-grained power estimation in multicore Systems on Chips (SoCs) is crucial for efficient thermal management. BPI (Blind Power Identification) is a recent approach that determines the power consumption of different cores and the thermal model of th
Externí odkaz:
http://arxiv.org/abs/2410.21261
Distracted driving is a critical safety issue that leads to numerous fatalities and injuries worldwide. This study addresses the urgent need for efficient and real-time machine learning models to detect distracted driving behaviors. Leveraging the Pr
Externí odkaz:
http://arxiv.org/abs/2410.15602
This work focuses on advancing security research in the hardware design space by formally defining the realistic problem of Hardware Trojan (HT) detection. The goal is to model HT detection more closely to the real world, i.e., describing the problem
Externí odkaz:
http://arxiv.org/abs/2410.15550
Active learning (AL) optimizes data labeling efficiency by selecting the most informative instances for annotation. A key component in this procedure is an acquisition function that guides the selection process and identifies the suitable instances f
Externí odkaz:
http://arxiv.org/abs/2410.04275
Modern multicore System-on-Chips (SoCs) feature hardware monitoring mechanisms that measure total power consumption. However, these aggregate measurements are often insufficient for fine-grained thermal and power management. This paper presents an en
Externí odkaz:
http://arxiv.org/abs/2409.18921
Autor:
Cornacchia, Giandomenico, Zizzo, Giulio, Fraser, Kieran, Hameed, Muhammad Zaid, Rawat, Ambrish, Purcell, Mark
The proliferation of Large Language Models (LLMs) in diverse applications underscores the pressing need for robust security measures to thwart potential jailbreak attacks. These attacks exploit vulnerabilities within LLMs, endanger data integrity and
Externí odkaz:
http://arxiv.org/abs/2409.17699
Autor:
Rawat, Ambrish, Schoepf, Stefan, Zizzo, Giulio, Cornacchia, Giandomenico, Hameed, Muhammad Zaid, Fraser, Kieran, Miehling, Erik, Buesser, Beat, Daly, Elizabeth M., Purcell, Mark, Sattigeri, Prasanna, Chen, Pin-Yu, Varshney, Kush R.
As generative AI, particularly large language models (LLMs), become increasingly integrated into production applications, new attack surfaces and vulnerabilities emerge and put a focus on adversarial threats in natural language and multi-modal system
Externí odkaz:
http://arxiv.org/abs/2409.15398
Spurious correlations are a major source of errors for machine learning models, in particular when aiming for group-level fairness. It has been recently shown that a powerful approach to combat spurious correlations is to re-train the last layer on a
Externí odkaz:
http://arxiv.org/abs/2409.14637