Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Barazandeh, Babak"'
We study the problem of finding approximate first-order stationary points in optimization problems of the form $\min_{x \in X} \max_{y \in Y} f(x,y)$, where the sets $X,Y$ are convex and $Y$ is compact. The objective function $f$ is smooth, but assum
Externí odkaz:
http://arxiv.org/abs/2110.03950
Publikováno v:
Signal Processing Volume 189, December 2021, 108245
Min-max saddle point games have recently been intensely studied, due to their wide range of applications, including training Generative Adversarial Networks (GANs). However, most of the recent efforts for solving them are limited to special regimes s
Externí odkaz:
http://arxiv.org/abs/2106.06075
Mixed linear regression (MLR) model is among the most exemplary statistical tools for modeling non-linear distributions using a mixture of linear models. When the additive noise in MLR model is Gaussian, Expectation-Maximization (EM) algorithm is a w
Externí odkaz:
http://arxiv.org/abs/2105.05953
Adaptive momentum methods have recently attracted a lot of attention for training of deep neural networks. They use an exponential moving average of past gradients of the objective function to update both search directions and learning rates. However
Externí odkaz:
http://arxiv.org/abs/2104.12676
Autor:
Barazandeh, Babak, Razaviyayn, Meisam
Min-max saddle point games appear in a wide range of applications in machine leaning and signal processing. Despite their wide applicability, theoretical studies are mostly limited to the special convex-concave structure. While some recent works gene
Externí odkaz:
http://arxiv.org/abs/2003.08093
In recent years, Generative Adversarial Networks (GANs) have drawn a lot of attentions for learning the underlying distribution of data in various applications. Despite their wide applicability, training GANs is notoriously difficult. This difficulty
Externí odkaz:
http://arxiv.org/abs/1904.09775
Autor:
Fekri, Masoud, Barazandeh, Babak
Optimal capital allocation between different assets is an important financial problem, which is generally framed as the portfolio optimization problem. General models include the single-period and multi-period cases. The traditional Mean-Variance mod
Externí odkaz:
http://arxiv.org/abs/1903.06632
Autor:
Barazandeh, Babak, Rafieisakhaei, Mohammadhussein, Kim, Sunwook, Zhenyu, Kong, Nussbaum, Maury A.
Classification methods based on sparse estimation have drawn much attention recently, due to their effectiveness in processing high-dimensional data such as images. In this paper, a method to improve the performance of a sparse representation classif
Externí odkaz:
http://arxiv.org/abs/1810.09447
Autor:
Barazandeh, Babak, Razaviyayn, Meisam
Finite mixture models are among the most popular statistical models used in different data science disciplines. Despite their broad applicability, inference under these models typically leads to computationally challenging non-convex problems. While
Externí odkaz:
http://arxiv.org/abs/1809.08705
Publikováno v:
Energy Exploration & Exploitation, 2016 Jan 01. 34(1), 19-41.
Externí odkaz:
https://www.jstor.org/stable/90007217
