Zobrazeno 1 - 10
of 36 918
pro vyhledávání: '"Sattar, A"'
Autor:
Vakili, Sattar, Olkhovskaya, Julia
Reinforcement learning utilizing kernel ridge regression to predict the expected value function represents a powerful method with great representational capacity. This setting is a highly versatile framework amenable to analytical results. We conside
Externí odkaz:
http://arxiv.org/abs/2410.23498
Multi-Layer Perceptrons (MLP) are powerful tools for representing complex, non-linear relationships, making them essential for diverse machine learning and AI applications. Efficient hardware implementation of MLPs can be achieved through many hardwa
Externí odkaz:
http://arxiv.org/abs/2410.10545
We investigate the effect of a Heaviside cut-off on the front propagation dynamics of the so-called Burgers-FisherKolmogoroff-Petrowskii-Piscounov (Burgers-FKPP) advection-reaction-diffusion equation. We prove the existence and uniqueness of a travel
Externí odkaz:
http://arxiv.org/abs/2410.08763
The limited energy available in most embedded systems poses a significant challenge in enhancing the performance of embedded processors and microcontrollers. One promising approach to address this challenge is the use of approximate computing, which
Externí odkaz:
http://arxiv.org/abs/2410.07027
The demand for energy-efficient and high performance embedded systems drives the evolution of new hardware architectures, including concepts like approximate computing. This paper presents a novel reconfigurable embedded platform named "phoeniX", usi
Externí odkaz:
http://arxiv.org/abs/2410.00622
We consider the problem of learning a realization of a partially observed dynamical system with linear state transitions and bilinear observations. Under very mild assumptions on the process and measurement noises, we provide a finite time analysis f
Externí odkaz:
http://arxiv.org/abs/2409.16499
Autor:
Karimi, Ahmad Maroof, Maiterth, Matthias, Shin, Woong, Sattar, Naw Safrin, Lu, Hao, Wang, Feiyi
In the face of surging power demands for exascale HPC systems, this work tackles the critical challenge of understanding the impact of software-driven power management techniques like Dynamic Voltage and Frequency Scaling (DVFS) and Power Capping. Th
Externí odkaz:
http://arxiv.org/abs/2408.01552
Semantic segmentation, as a crucial component of complex visual interpretation, plays a fundamental role in autonomous vehicle vision systems. Recent studies have significantly improved the accuracy of semantic segmentation by exploiting complementar
Externí odkaz:
http://arxiv.org/abs/2407.01328
Autor:
Vakili, Sattar
Reinforcement Learning (RL) has shown great empirical success in various application domains. The theoretical aspects of the problem have been extensively studied over past decades, particularly under tabular and linear Markov Decision Process struct
Externí odkaz:
http://arxiv.org/abs/2406.15250
Autor:
Islam, Md. Shariful, Shaqib, SM, Ramit, Shahriar Sultan, Khushbu, Shahrun Akter, Sattar, Abdus, Noori, Sheak Rashed Haider
In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and foo
Externí odkaz:
http://arxiv.org/abs/2406.07707