Zobrazeno 1 - 10
of 34 017
pro vyhledávání: '"Adibi A"'
This paper addresses the problem of detecting changes when only unnormalized pre- and post-change distributions are accessible. This situation happens in many scenarios in physics such as in ferromagnetism, crystallography, magneto-hydrodynamics, and
Externí odkaz:
http://arxiv.org/abs/2410.14615
Autor:
Taghinejad, Hossein, Taghinejad, Mohammad, Abdollahramezani, Sajjad, Li, Qitong, Woods, Eric V., Tian, Mengkun, Eftekhar, Ali A., Lyu, Yuanqi, Zhang, Xiang, Ajayan, Pulickel M., Cai, Wenshan, Brongersma, Mark L., Analytis, James G., Adibi, Ali
Achieving deterministic control over the properties of low-dimensional materials with nanoscale precision is a long-sought goal. Mastering this capability has a transformative impact on the design of multifunctional electrical and optical devices. He
Externí odkaz:
http://arxiv.org/abs/2410.06181
Plastic waste in aquatic environments poses severe risks to marine life and human health. Autonomous robots can be utilized to collect floating waste, but they require accurate object identification capability. While deep learning has been widely use
Externí odkaz:
http://arxiv.org/abs/2409.12659
Recent research endeavours have theoretically shown the beneficial effect of cooperation in multi-agent reinforcement learning (MARL). In a setting involving $N$ agents, this beneficial effect usually comes in the form of an $N$-fold linear convergen
Externí odkaz:
http://arxiv.org/abs/2407.20441
Depression is a common mental health issue that requires prompt diagnosis and treatment. Despite the promise of social media data for depression detection, the opacity of employed deep learning models hinders interpretability and raises bias concerns
Externí odkaz:
http://arxiv.org/abs/2407.21041
Autor:
Fabbro, Nicolò Dal, Adibi, Arman, Poor, H. Vincent, Kulkarni, Sanjeev R., Mitra, Aritra, Pappas, George J.
We consider a setting in which $N$ agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server. We assume that the up-link transmissions to the server are subject to asynchronous
Externí odkaz:
http://arxiv.org/abs/2403.17247
Meta-learning problem is usually formulated as a bi-level optimization in which the task-specific and the meta-parameters are updated in the inner and outer loops of optimization, respectively. However, performing the optimization in the Riemannian s
Externí odkaz:
http://arxiv.org/abs/2402.18605
Autor:
Adibi, Arman, Fabbro, Nicolo Dal, Schenato, Luca, Kulkarni, Sanjeev, Poor, H. Vincent, Pappas, George J., Hassani, Hamed, Mitra, Aritra
Motivated by applications in large-scale and multi-agent reinforcement learning, we study the non-asymptotic performance of stochastic approximation (SA) schemes with delayed updates under Markovian sampling. While the effect of delays has been exten
Externí odkaz:
http://arxiv.org/abs/2402.11800
Publikováno v:
Environmental Health Perspectives, 2010 Mar 01. 118(3), A111-A111.
Externí odkaz:
https://www.jstor.org/stable/25615009
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract When studying the working memory (WM), the ‘slot model’ and the ‘resource model’ are two main theories used to describe how information retention occurs. The slot model shows that WM capacity consists of a certain number of predefine
Externí odkaz:
https://doaj.org/article/320876c794b845b98fbd4e0bd031e276