no code implementations • 16 Apr 2014 • Navodit Misra, Ercan E. Kuruoglu
Stable random variables are motivated by the central limit theorem for densities with (potentially) unbounded variance and can be thought of as natural generalizations of the Gaussian distribution to skewed and heavy-tailed phenomenon.
no code implementations • 11 Apr 2019 • Vignesh Srinivasan, Ercan E. Kuruoglu, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima
Many existing methods employ Gaussian random variables for exploring the data space to find the most adversarial (for attacking) or least adversarial (for defense) point.
1 code implementation • 15 Jun 2020 • Oktay Karakuş, Ercan E. Kuruoglu, Alin Achim
In this paper, we present a novel statistical model, $\textit{the generalized-Gaussian-Rician}$ (GG-Rician) distribution, for the characterization of synthetic aperture radar (SAR) images.
1 code implementation • NeurIPS 2020 • Zifeng Wang, Xi Chen, Rui Wen, Shao-Lun Huang, Ercan E. Kuruoglu, Yefeng Zheng
Counterfactual learning for dealing with missing-not-at-random data (MNAR) is an intriguing topic in the recommendation literature since MNAR data are ubiquitous in modern recommender systems.
1 code implementation • ICLR 2022 • Zifeng Wang, Shao-Lun Huang, Ercan E. Kuruoglu, Jimeng Sun, Xi Chen, Yefeng Zheng
Then, we build an IIW-based information bottleneck on the trade-off between accuracy and information complexity of NNs, namely PIB.
no code implementations • 15 Jan 2022 • Yi Yan, Ercan E. Kuruoglu, Mustafa A. Altınkaya
Recently introduced graph adaptive least mean squares algorithm is unstable under non-Gaussian impulsive noise and has high computational complexity.
no code implementations • 19 Mar 2022 • Zhendong Shi, Ercan E. Kuruoglu, Xiaoli Wei
In algorithm optimization in reinforcement learning, how to deal with the exploration-exploitation dilemma is particularly important.
no code implementations • 15 Mar 2023 • Hengxi Zhang, Zhendong Shi, Yuanquan Hu, Wenbo Ding, Ercan E. Kuruoglu, Xiao-Ping Zhang
Quantitative markets are characterized by swift dynamics and abundant uncertainties, making the pursuit of profit-driven stock trading actions inherently challenging.
no code implementations • 1 Oct 2023 • Zhendong Shi, Xiaoli Wei, Ercan E. Kuruoglu
The problem of how to take the right actions to make profits in sequential process continues to be difficult due to the quick dynamics and a significant amount of uncertainty in many application scenarios.