Zobrazeno 1 - 10
of 10 937
pro vyhledávání: '"P. P. Pandit"'
Autor:
Islam, Md Mirajul, Uddin, Md Nahiyan, Hasana, Maoyejatun, Pandit, Debojit, Rahman, Nafis Mahmud, Chellappan, Sriram, Azam, Sami, Islam, A. B. M. Alim Al
People exhibit unique emotional responses. In the same scenario, the emotional reactions of two individuals can be either similar or vastly different. For instance, consider one person's reaction to an invitation to smoke versus another person's resp
Externí odkaz:
http://arxiv.org/abs/2412.19041
The EU GDPR is a landmark regulation that introduced several rights for individuals to obtain information and control how their personal data is being processed, as well as receive a copy of it. However, there are gaps in the effective use of rights
Externí odkaz:
http://arxiv.org/abs/2412.15451
Autor:
Bhaskar, Umang, Pandit, Yeshwant
The existence of EFX allocations is one of the most significant open questions in fair division. Recent work by Christodolou, Fiat, Koutsoupias, and Sgouritsa ("Fair allocation in graphs", EC 2023) establishes the existence of EFX allocations for gra
Externí odkaz:
http://arxiv.org/abs/2412.06513
In the fair division of items among interested agents, envy-freeness is possibly the most favoured and widely studied formalisation of fairness. For indivisible items, envy-free allocations may not exist in trivial cases, and hence research and pract
Externí odkaz:
http://arxiv.org/abs/2411.19881
Classical kernel machines have historically faced significant challenges in scaling to large datasets and model sizes--a key ingredient that has driven the success of neural networks. In this paper, we present a new methodology for building kernel ma
Externí odkaz:
http://arxiv.org/abs/2411.16658
We show that flocking of microswimmers in a turbulent flow can enhance the efficacy of reinforcement-learning-based path-planning of microswimmers in turbulent flows. In particular, we develop a machine-learning strategy that incorporates Vicsek-mode
Externí odkaz:
http://arxiv.org/abs/2411.15902
Recent advances in machine learning have led to increased interest in reproducing kernel Banach spaces (RKBS) as a more general framework that extends beyond reproducing kernel Hilbert spaces (RKHS). These works have resulted in the formulation of re
Externí odkaz:
http://arxiv.org/abs/2411.11242
This systematic review explores the theoretical foundations, evolution, applications, and future potential of Kolmogorov-Arnold Networks (KAN), a neural network model inspired by the Kolmogorov-Arnold representation theorem. KANs distinguish themselv
Externí odkaz:
http://arxiv.org/abs/2411.06078
We explore the relationship between complexity and duality in quantum systems, focusing on how local and non-local operators evolve under time evolution. We find that non-local operators, which are dual to local operators under specific mappings, exh
Externí odkaz:
http://arxiv.org/abs/2411.02546
Despite the popularity of large language model (LLM) quantization for inference acceleration, significant uncertainty remains regarding the accuracy-performance trade-offs associated with various quantization formats. We present a comprehensive empir
Externí odkaz:
http://arxiv.org/abs/2411.02355