Zobrazeno 1 - 10
of 7 235
pro vyhledávání: '"Kumar, A. R."'
Autor:
Surrow, Jeppe H., Thomsen, Simon T., Kumar, Rakesh R., Brusatori, Mónica Far, Montes, Maria Paula, Hoede, Chris, Klein, Holger N., Volet, Nicolas
A standard method to reduce the linewidth of semiconductor lasers involves the use of external optical feedback (EOF). However, feedback powers less than 1 % usually trigger coherence collapse (CC), leading to chaotic laser dynamics and linewidth bro
Externí odkaz:
http://arxiv.org/abs/2410.08621
This study addresses the transmission value of energy storage in electric grids. The inherent connection between storage and transmission infrastructure is captured from a "cumulative energy" perspective, which enables the reformulating of the conven
Externí odkaz:
http://arxiv.org/abs/2407.09428
This work focuses on the entropy-regularized independent natural policy gradient (NPG) algorithm in multi-agent reinforcement learning. In this work, agents are assumed to have access to an oracle with exact policy evaluation and seek to maximize the
Externí odkaz:
http://arxiv.org/abs/2405.02769
We study Markov potential games under the infinite horizon average reward criterion. Most previous studies have been for discounted rewards. We prove that both algorithms based on independent policy gradient and independent natural policy gradient co
Externí odkaz:
http://arxiv.org/abs/2403.05738
We consider the community recovery problem on a one-dimensional random geometric graph where every node has two independent labels: an observed location label and a hidden community label. A geometric kernel maps the locations of pairs of nodes to pr
Externí odkaz:
http://arxiv.org/abs/2403.02802
Autor:
Kumar, B. R. Vinay, Leskelä, Lasse
This work studies queues in a Euclidean space. Consider $N$ servers that are distributed uniformly in $[0,1]^d$. Customers arrive at the servers according to independent stationary processes. Upon arrival, they probabilistically decide whether to joi
Externí odkaz:
http://arxiv.org/abs/2402.13192
Autor:
Raksha, Kumar, B. R. Srivatsa
In the present work, we established continued fractions of level eighteen, twenty six and thirty. Further, we obtained vanishing coefficients and many algebraic relations. To validate our result colored partitions are also obtained.
Externí odkaz:
http://arxiv.org/abs/2311.06298
We consider the infinite-horizon linear Markov Decision Processes (MDPs), where the transition probabilities of the dynamic model can be linearly parameterized with the help of a predefined low-dimensional feature mapping. While the existing regressi
Externí odkaz:
http://arxiv.org/abs/2310.11515
This work studies an independent natural policy gradient (NPG) algorithm for the multi-agent reinforcement learning problem in Markov potential games. It is shown that, under mild technical assumptions and the introduction of the \textit{suboptimalit
Externí odkaz:
http://arxiv.org/abs/2310.09727
Publikováno v:
Electronic Journal of Plant Breeding, Vol 15, Iss 3, Pp 680-688 (2024)
The present study consisted of total 45 hybrids along with 18 parents and 2 checks. These entries were evaluated in randomized block design with three replications over three locations. Observations were recorded on ten characters to study per se per
Externí odkaz:
https://doaj.org/article/f98cb1ad553d4569942880268c7d0e64
