Zobrazeno 1 - 10
of 303
pro vyhledávání: '"Srivastava Shashank"'
Autor:
Srivastava Shashank, Dutt Amit, Helena Raj Vijilius, Sri Lalitha Y., Kalita Das Karabi, Saleh Mashkour Muthana, Kumar Ch. Srivardhan
Publikováno v:
E3S Web of Conferences, Vol 552, p 01114 (2024)
The recent world is being focused on deriving methods for using renewable energy-based systems to meet the energy demands. There are various research areas to be focused upon for making the output from these energy systems more reliable and efficient
Externí odkaz:
https://doaj.org/article/769b295215b04299b2cbf5b22d2152ae
Autor:
Srivastava Shashank, Asha V., B Navajyoth, Nijhawan Ginni, Krishna P.V.V.S.S.R., Al-Saady Fouad A., Rao K. Nishanth
Publikováno v:
E3S Web of Conferences, Vol 552, p 01115 (2024)
Promoting construction, enhancing safety and multiple functions of IoT. Since the beginning of Fourth Industrial Revolution, digitalization becomes a fundamental function of all the construction project and bring all the project to a brand new practi
Externí odkaz:
https://doaj.org/article/c894eb5b463a4896a8e0702fa0678dfc
Autor:
Srivastava Shashank, Kumar Indradeep, Kumar Manish, Shakier Hussein Ghafel, B Swathi, Chahuan Neeraj
Publikováno v:
E3S Web of Conferences, Vol 505, p 01027 (2024)
This research paper explores the opportunities and challenges associated with the use of machine learning and artificial intelligence in advanced materials processing. With the exponential growth of data, advanced analytical techniques and powerful c
Externí odkaz:
https://doaj.org/article/a77ce891b96641cf8efef24eb000ee62
Autor:
Ozden, Tarik Can, Kara, Ozgur, Akcin, Oguzhan, Zaman, Kerem, Srivastava, Shashank, Chinchali, Sandeep P., Rehg, James M.
Current image immunization defense techniques against diffusion-based editing embed imperceptible noise in target images to disrupt editing models. However, these methods face scalability challenges, as they require time-consuming re-optimization for
Externí odkaz:
http://arxiv.org/abs/2411.17957
Autor:
Bergamaschi, Thiago, Jeronimo, Fernando Granha, Mittal, Tushant, Srivastava, Shashank, Tulsiani, Madhur
We give a construction of Quantum Low-Density Parity Check (QLDPC) codes with near-optimal rate-distance tradeoff and efficient list decoding up to the Johnson bound in polynomial time. Previous constructions of list decodable good distance quantum c
Externí odkaz:
http://arxiv.org/abs/2411.04306
Autor:
Menon, Rakesh R., Srivastava, Shashank
Despite their high predictive accuracies, current machine learning systems often exhibit systematic biases stemming from annotation artifacts or insufficient support for certain classes in the dataset. Recent work proposes automatic methods for ident
Externí odkaz:
http://arxiv.org/abs/2410.22239
Autor:
Srivastava, Shashank
Folded Reed-Solomon (FRS) codes are variants of Reed-Solomon codes, known for their optimal list decoding radius. We show explicit FRS codes with rate $R$ that can be list decoded up to radius $1-R-\epsilon$ with lists of size $\mathcal{O}(1/ \epsilo
Externí odkaz:
http://arxiv.org/abs/2410.09031
While much research has explored enhancing the reasoning capabilities of large language models (LLMs) in the last few years, there is a gap in understanding the alignment of these models with social values and norms. We introduce the task of judging
Externí odkaz:
http://arxiv.org/abs/2410.08698
Autor:
Srivastava, Shashank
Error-correcting codes are one of the most fundamental objects in pseudorandomness, with applications in communication, complexity theory, and beyond. Codes are useful because of their ability to support decoding, which is the task of recovering a co
Externí odkaz:
http://arxiv.org/abs/2408.14652
Model fusion research aims to aggregate the knowledge of multiple individual models to enhance performance by combining their weights. In this work, we study the inverse problem: investigating whether model fusion can be used to reduce unwanted knowl
Externí odkaz:
http://arxiv.org/abs/2311.07682