Optimal and Adaptive Estimation of Extreme Values in the Permuted Monotone Matrix Model. (arXiv:1911.12516v1 [math.ST])

Mathematics (math), ScienceLeave a comment

Motivated by applications in metagenomics, we consider the permuted monotone matrix model $Y=\Theta\Pi+Z$, where $Y\in \mathbb{R}^{n\times p}$ is observed, $\Theta\in \mathbb{R}^{n\times p}$ is an unknown signal matrix with monotone rows, $\Pi \in \mathbb{R}^{p\times p}$ is an unknown permutation matrix, and $Z\in \mathbb{R}^{n\times p}$ is the noise matrix. This paper studies the estimation of the extreme…

Serverless seismic imaging in the cloud. (arXiv:1911.12447v1 [cs.DC])

Computer Science, ScienceLeave a comment

This abstract presents a serverless approach to seismic imaging in the cloud based on high-throughput containerized batch processing, event-driven computations and a domain-specific language compiler for solving the underlying wave equations. A 3D case study on Azure demonstrates that this approach allows reducing the operating cost of up to a factor of 6, making the…

Empirical Upper-bound in Object Detection and More. (arXiv:1911.12451v1 [cs.CV])

Computer Science, ScienceLeave a comment

Object detection remains as one of the most notorious open problems in computer vision. Despite large strides in accuracy in recent years, modern object detectors have started to saturate on popular benchmarks raising the question of how far we can reach with deep learning tools and tricks. Here, by employing 2 state-of-the-art object detection benchmarks,…

Android Botnet Detection using Convolutional Neural Networks. (arXiv:1911.12457v1 [cs.NE])

Computer Science, ScienceLeave a comment

Today, Android devices are able to provide various services. They support applications for different purposes such as entertainment, business, health, education, and banking services. Because of the functionality and popularity of Android devices as well as the open-source policy of Android OS, they have become a suitable target for attackers. Android Botnet is one of…

Collecting Charges for Ad Impact on User Experience for Different Price Types. (arXiv:1911.12458v1 [cs.GT])

Computer Science, ScienceLeave a comment

This note describes how to collect charges for ad impact on user experience. The charge may be per-view, to account for impact on user experience from viewing an ad, or per-click, to account for impact from clicking on the ad. The results for per-click charges also apply to per-conversion charges or per-action charges. Conceivably, a…

Information-Geometric Set Embeddings (IGSE): From Sets to Probability Distributions. (arXiv:1911.12463v1 [cs.LG])

Computer Science, ScienceLeave a comment

This letter introduces an abstract learning problem called the “set embedding”: The objective is to map sets into probability distributions so as to lose less information. We relate set union and intersection operations with corresponding interpolations of probability distributions. We also demonstrate a preliminary solution with experimental results on toy set embedding examples.

The Microstructure of Stochastic Volatility Models with Self-Exciting Jump Dynamics. (arXiv:1911.12969v1 [q-fin.MF])

Quantitative Finance, ScienceLeave a comment

We provide a general probabilistic framework within which we establish scaling limits for a class of continuous-time stochastic volatility models with self-exciting jump dynamics. In the scaling limit, the joint dynamics of asset returns and volatility is driven by independent Gaussian white noises and two independent Poisson random measures that capture the arrival of exogenous…

The equivalent CEV volatility of the SABR model. (arXiv:1911.13123v1 [q-fin.MF])

Quantitative Finance, ScienceLeave a comment

This study presents new analytic approximations of the stochastic-alpha-beta-rho (SABR) model. Unlike existing studies that focus on the equivalent Black-Scholes (BS) volatility, we instead derive the equivalent volatility under the constant-elasticity-of-variance (CEV) model, which is the limit of the SABR model when the volatility of volatility approaches 0. Numerical examples demonstrate the accuracy of the…

Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019. (arXiv:1911.13288v1 [cs.LG])

Quantitative Finance, ScienceLeave a comment

Financial time series forecasting is, without a doubt, the top choice of computational intelligence for finance researchers from both academia and financial industry due to its broad implementation areas and substantial impact. Machine Learning (ML) researchers came up with various models and a vast number of studies have been published accordingly. As such, a significant…