Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Stosic, Darko"'
This work maps deep neural networks to classical Ising spin models, allowing them to be described using statistical thermodynamics. The density of states shows that structures emerge in the weights after they have been trained -- well-trained network
Externí odkaz:
http://arxiv.org/abs/2209.08678
A novel heuristic approach is proposed here for time series data analysis, dubbed Generalized weighted permutation entropy, which amalgamates and generalizes beyond their original scope two well established data analysis methods: Permutation entropy,
Externí odkaz:
http://arxiv.org/abs/2207.01169
Stock markets can become inefficient due to calendar anomalies known as day-of-the-week effect. Calendar anomalies are well-known in financial literature, but the phenomena remain to be explored in econophysics. In this paper we use multifractal anal
Externí odkaz:
http://arxiv.org/abs/2106.06164
Distance metric learning has attracted a lot of interest for solving machine learning and pattern recognition problems over the last decades. In this work we present a simple approach based on concepts from statistical physics to learn optimal distan
Externí odkaz:
http://arxiv.org/abs/2106.05495
Autor:
Stosic, Darko, Stosic, Dusan
While larger neural models are pushing the boundaries of what deep learning can do, often more weights are needed to train models rather than to run inference for tasks. This paper seeks to understand this behavior using search spaces -- adding weigh
Externí odkaz:
http://arxiv.org/abs/2105.12920
Autor:
Mishra, Asit, Latorre, Jorge Albericio, Pool, Jeff, Stosic, Darko, Stosic, Dusan, Venkatesh, Ganesh, Yu, Chong, Micikevicius, Paulius
As neural network model sizes have dramatically increased, so has the interest in various techniques to reduce their parameter counts and accelerate their execution. An active area of research in this field is sparsity - encouraging zero values in pa
Externí odkaz:
http://arxiv.org/abs/2104.08378
Stock market indices are one of the most investigated complex systems in econophysics. Here we extend the existing literature on stock markets in connection with nonextensive statistical mechanics. We explore the nonextensivity of price volatilities
Externí odkaz:
http://arxiv.org/abs/1901.07721
Publikováno v:
In Journal of Visual Communication and Image Representation August 2019 63
Publikováno v:
In Physica A: Statistical Mechanics and its Applications 1 July 2019 525:548-556
Publikováno v:
In Physica A: Statistical Mechanics and its Applications 1 July 2019 525:956-964