Zobrazeno 1 - 10
of 15 067
pro vyhledávání: '"Sharifi, P."'
This paper presents a novel reinforcement learning framework for trajectory tracking of unmanned aerial vehicles in cluttered environments using a dual-agent architecture. Traditional optimization methods for trajectory tracking face significant comp
Externí odkaz:
http://arxiv.org/abs/2410.23571
Neural Architecture Search (NAS) methods autonomously discover high-accuracy neural network architectures, outperforming manually crafted ones. However, The NAS methods require high computational costs due to the high dimension search space and the n
Externí odkaz:
http://arxiv.org/abs/2410.22487
Autor:
Drijvers, Manu, Gretler, Tim, Harchol, Yotam, Klenze, Tobias, Maric, Ognjen, Neamtu, Stefan, Pignolet, Yvonne-Anne, Rumenov, Rostislav, Sharifi, Daniel, Shoup, Victor
Byzantine fault tolerant (BFT) protocol descriptions often assume application-layer networking primitives, such as best-effort and reliable broadcast, which are impossible to implement in practice in a Byzantine environment as they require either unb
Externí odkaz:
http://arxiv.org/abs/2410.22080
Autor:
Hajiaghayi, MohammadTaghi, Jahan, Shayan Chashm, Sharifi, Mohammad, Shin, Suho, Springer, Max
The online bipartite matching problem, extensively studied in the literature, deals with the allocation of online arriving vertices (items) to a predetermined set of offline vertices (agents). However, little attention has been given to the concept o
Externí odkaz:
http://arxiv.org/abs/2410.19163
Autor:
Sharifi, Mehran
Publikováno v:
J Math Techniques Comput Math, 3(10), 1-14 (2024)
The study of Large-Eddy Simulations (LES) in turbulent flows continues to be a critical area of research, particularly in understanding the behavior of small-scale turbulence structures and their impact on resolved scales. In this study, we focus on
Externí odkaz:
http://arxiv.org/abs/2410.16753
Autor:
Sharifi, Mehran
Publikováno v:
J Math Techniques Comput Math, 3(10), 01-20 (2024)
This study presents an efficient algebraic scheme known as MULES for sharp interface advection, verified against various schemes including first-order upwind, second-order central, van Leer flux limiter, and Geometric Volume-of-Fluid (VOF). Two probl
Externí odkaz:
http://arxiv.org/abs/2410.16754
Time series~(TS) modeling is essential in dynamic systems like weather prediction and anomaly detection. Recent studies utilize Large Language Models (LLMs) for TS modeling, leveraging their powerful pattern recognition capabilities. These methods pr
Externí odkaz:
http://arxiv.org/abs/2410.16489
In strategic classification, agents manipulate their features, at a cost, to receive a positive classification outcome from the learner's classifier. The goal of the learner in such settings is to learn a classifier that is robust to strategic manipu
Externí odkaz:
http://arxiv.org/abs/2410.02513
Quantifying fiber disarray, which is a prominent maladaptation associated with hypertrophic cardiomyopathy, remains critical to understanding the disease's complex pathophysiology. This study investigates the role of heterogeneous impairment of fiber
Externí odkaz:
http://arxiv.org/abs/2409.15508
This paper introduces an innovative keypoint detection technique based on Convolutional Neural Networks (CNNs) to enhance the performance of existing Deep Visual Servoing (DVS) models. To validate the convergence of the Image-Based Visual Servoing (I
Externí odkaz:
http://arxiv.org/abs/2409.13668