Zobrazeno 1 - 10
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pro vyhledávání: '"Pasricha A"'
The rapid proliferation of deep learning has revolutionized computing hardware, driving innovations to improve computationally expensive multiply-and-accumulate operations in deep neural networks. Among these innovations are integrated silicon-photon
Externí odkaz:
http://arxiv.org/abs/2411.16712
Machine learning (ML) based indoor localization solutions are critical for many emerging applications, yet their efficacy is often compromised by hardware/software variations across mobile devices (i.e., device heterogeneity) and the threat of ML dat
Externí odkaz:
http://arxiv.org/abs/2411.09055
This study is the first to explore the application of a time-series foundation model for Value-at-Risk (VaR) estimation. Foundation models, pre-trained on vast and varied datasets, can be used in a zero-shot setting with relatively minimal data or fu
Externí odkaz:
http://arxiv.org/abs/2410.11773
In this article, we employ physics-informed residual learning (PIRL) and propose a pricing method for European options under a regime-switching framework, where closed-form solutions are not available. We demonstrate that the proposed approach serves
Externí odkaz:
http://arxiv.org/abs/2410.10474
Function-as-a-Service (FaaS) is a growing cloud computing paradigm that is expected to reduce the user cost of service over traditional serverful approaches. However, the environmental impact of FaaS has not received much attention. We investigate Fa
Externí odkaz:
http://arxiv.org/abs/2410.11875
Autor:
Khan, Kamil, Pasricha, Sudeep
In emerging high-performance Network-on-Chip (NoC) architectures, efficient power management is crucial to minimize energy consumption. We propose a novel framework called CAFEEN that employs both heuristic-based fine-grained and machine learning-bas
Externí odkaz:
http://arxiv.org/abs/2410.07426
Autor:
Briscoe-Martinez, Gilberto, Pasricha, Anuj, Abderezaei, Ava, Chaganti, Santosh, Vajrala, Sarath Chandra, Popuri, Sri Kanth, Roncone, Alessandro
This work explores non-prehensile manipulation (NPM) and whole-body interaction as strategies for enabling robotic manipulators to conduct manipulation tasks despite experiencing locked multi-joint (LMJ) failures. LMJs are critical system faults wher
Externí odkaz:
http://arxiv.org/abs/2410.01102
Autor:
Pasricha, Anuj, Roncone, Alessandro
Motion planning for articulated robots has traditionally been governed by algorithms that operate within manufacturer-defined payload limits. Our empirical analysis of the Franka Emika Panda robot demonstrates that this approach unnecessarily restric
Externí odkaz:
http://arxiv.org/abs/2409.18939
Serverless computing is an emerging cloud computing paradigm that can reduce costs for cloud providers and their customers. However, serverless cloud platforms have stringent performance requirements (due to the need to execute short duration functio
Externí odkaz:
http://arxiv.org/abs/2409.00550
Autor:
Pasricha, Sudeep
Indoor navigation is a foundational technology to assist the tracking and localization of humans, autonomous vehicles, drones, and robots in indoor spaces. Due to the lack of penetration of GPS signals in buildings, subterranean locales, and dense ur
Externí odkaz:
http://arxiv.org/abs/2408.04797