Zobrazeno 1 - 10
of 25 872
pro vyhledávání: '"A A, Massoud"'
Autor:
Abdellatif, Alaa Awad, Elmancy, Ali, Mohamed, Amr, Massoud, Ahmed, Lebda, Wadha, Naji, Khalid K.
This paper introduces a comprehensive framework for Post-Disaster Search and Rescue (PDSR), aiming to optimize search and rescue operations leveraging Unmanned Aerial Vehicles (UAVs). The primary goal is to improve the precision and availability of s
Externí odkaz:
http://arxiv.org/abs/2410.22982
This paper presents a CMOS-compatible Lechner-Hauke-Zoller (LHZ)--based analog tile structure as a fundamental unit for developing scalable analog Ising machines (IMs). In the designed LHZ tile, the voltage-controlled oscillators are employed as the
Externí odkaz:
http://arxiv.org/abs/2410.16079
Autor:
Voelcker, Claas A, Hussing, Marcel, Eaton, Eric, Farahmand, Amir-massoud, Gilitschenski, Igor
Building deep reinforcement learning (RL) agents that find a good policy with few samples has proven notoriously challenging. To achieve sample efficiency, recent work has explored updating neural networks with large numbers of gradient steps for eve
Externí odkaz:
http://arxiv.org/abs/2410.08896
This paper presents a mixed-signal neuromorphic accelerator architecture designed for accelerating inference with event-based neural network models. This fully CMOS-compatible accelerator utilizes analog computing to emulate synapse and neuron operat
Externí odkaz:
http://arxiv.org/abs/2410.08403
In this paper, we propose a framework to enhance the robustness of the neural models by mitigating the effects of process-induced and aging-related variations of analog computing components on the accuracy of the analog neural networks. We model thes
Externí odkaz:
http://arxiv.org/abs/2409.18553
Autor:
Khanaki, Karim, Pourmahdian, Massoud
The main purpose of this paper is to present new and more uniform model-theoretic/combinatorial proofs of the theorems (in [5] and [4]): The randomization $T^{R}$ of a complete first-order theory $T$ with $NIP$/stability is a (complete) first-order c
Externí odkaz:
http://arxiv.org/abs/2408.15014
In this paper, we present a YOLO-based framework for layout hotspot detection, aiming to enhance the efficiency and performance of the design rule checking (DRC) process. Our approach leverages the YOLOv8 vision model to detect multiple hotspots with
Externí odkaz:
http://arxiv.org/abs/2407.14498
Vision Transformers (ViTs) represent a groundbreaking shift in machine learning approaches to computer vision. Unlike traditional approaches, ViTs employ the self-attention mechanism, which has been widely used in natural language processing, to anal
Externí odkaz:
http://arxiv.org/abs/2407.12736
The Value Iteration (VI) algorithm is an iterative procedure to compute the value function of a Markov decision process, and is the basis of many reinforcement learning (RL) algorithms as well. As the error convergence rate of VI as a function of ite
Externí odkaz:
http://arxiv.org/abs/2407.10454
Long-horizon tasks, which have a large discount factor, pose a challenge for most conventional reinforcement learning (RL) algorithms. Algorithms such as Value Iteration and Temporal Difference (TD) learning have a slow convergence rate and become in
Externí odkaz:
http://arxiv.org/abs/2407.08803