Zobrazeno 1 - 10
of 9 460
pro vyhledávání: '"Murari A."'
Autor:
Chanyal, B. C., Murari, Sayyam
This study explores the application of quaternionic left and right-handed algebraic frameworks to discuss the neutrino-handedness behavior. The generalized left and right-handed Dirac equations are expressed in terms of quaternionic four-dimensional
Externí odkaz:
http://arxiv.org/abs/2410.05337
Autor:
Chundawat, Vikram S, Niroula, Pushkar, Dhungana, Prasanna, Schoepf, Stefan, Mandal, Murari, Brintrup, Alexandra
Federated learning (FL) has enabled collaborative model training across decentralized data sources or clients. While adding new participants to a shared model does not pose great technical hurdles, the removal of a participant and their related infor
Externí odkaz:
http://arxiv.org/abs/2410.04144
Recent research has seen significant interest in methods for concept removal and targeted forgetting in diffusion models. In this paper, we conduct a comprehensive white-box analysis to expose significant vulnerabilities in existing diffusion model u
Externí odkaz:
http://arxiv.org/abs/2409.05668
Continual learning and machine unlearning are crucial challenges in machine learning, typically addressed separately. Continual learning focuses on adapting to new knowledge while preserving past information, whereas unlearning involves selectively f
Externí odkaz:
http://arxiv.org/abs/2408.11374
This paper considers one of the fundamental parallel-in-time methods for the solution of ordinary differential equations, Parareal, and extends it by adopting a neural network as a coarse propagator. We provide a theoretical analysis of the convergen
Externí odkaz:
http://arxiv.org/abs/2408.09756
Unlearning methods for recommender systems (RS) have emerged to address privacy issues and concerns about legal compliance. However, evolving user preferences and content licensing issues still remain unaddressed. This is particularly true in case of
Externí odkaz:
http://arxiv.org/abs/2405.15328
Autor:
Robinson, Nathaniel R., Dabre, Raj, Shurtz, Ammon, Dent, Rasul, Onesi, Onenamiyi, Monroc, Claire Bizon, Grobol, Loïc, Muhammad, Hasan, Garg, Ashi, Etori, Naome A., Tiyyala, Vijay Murari, Samuel, Olanrewaju, Stutzman, Matthew Dean, Odoom, Bismarck Bamfo, Khudanpur, Sanjeev, Richardson, Stephen D., Murray, Kenton
A majority of language technologies are tailored for a small number of high-resource languages, while relatively many low-resource languages are neglected. One such group, Creole languages, have long been marginalized in academic study, though their
Externí odkaz:
http://arxiv.org/abs/2405.05376
Surface and strain engineering are among the cheaper ways to modulate structure property relations in materials. Due to their compositional flexibilities, MXenes, the family of two-dimensional materials, provide enough opportunity for surface enginee
Externí odkaz:
http://arxiv.org/abs/2403.13543
Autor:
Liu, Fang, Skruszewicz, Slawomir, Späthe, Julian, Zhang, Yinyu, Hell, Sebastian, Ying, Bo, Paulus, Gerhard G., Kiss, Bálint, Murari, Krishna, Khalil, Malin, Cormier, Eric, Jiao, Li Guang, Fritzsche, Stephan, Kübel, Matthias
Strong-field ionization can induce electron motion in both the continuum and the valence shell of the parent ion. Here, we explore their interplay by studying laser-induced electron diffraction (LIED) patterns arising from interaction with the potent
Externí odkaz:
http://arxiv.org/abs/2403.10473
Autor:
Tarun, Ayush K, Chundawat, Vikram S, Mandal, Murari, Tan, Hong Ming, Chen, Bowei, Kankanhalli, Mohan
Quantifying the value of data within a machine learning workflow can play a pivotal role in making more strategic decisions in machine learning initiatives. The existing Shapley value based frameworks for data valuation in machine learning are comput
Externí odkaz:
http://arxiv.org/abs/2402.09288