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Asset Management in Machine Learning: A Survey [article]

Samuel Idowu, Daniel Strüber, Thorsten Berger
2021 arXiv   pre-print
We present a feature-based survey of 17 tools with ML asset management support identified in a systematic search.  ...  Machine Learning (ML) techniques are becoming essential components of many software systems today, causing an increasing need to adapt traditional software engineering practices and tools to the development  ...  Data is an essential asset type in machine learning.  ... 
arXiv:2102.06919v2 fatcat:hutupxarpjg5flelyfhxgoc72m

Machine Learning in Automated Asset Management Processes 4.1

Marcus Becker, Mikhail Beketov, Manuel Wittke
2021 Die Unternehmung. Swiss Journal of Business Research and Practice  
The traditional (human driven) process of Asset Management has become automatized by algorithmic decision trading with so called Robo Advisors (RAs).  ...  With an increasing amount of publicly available financial data, the foundation for applying machine learning (ML) algorithms has been paved.  ...  Methods of Machine Learning-Algorithms suitable to Automated Asset Management 4.1 Machine Learning (ML) describes a set of methods that can automatically detect patterns in data, and then use the uncovered  ... 
doi:10.5771/0042-059x-2021-3-411 fatcat:ww5vahreurc3vdscdcx3h6m2vm

Machine Learning for Financial Risk Management: A Survey

Akib Mashrur, Wei Luo, Nayyar A. Zaidi, Antonio Robles-Kelly
2020 IEEE Access  
• We systematically survey a large corpus of existing literature on applying machine learning in risk management and reveal the best practices and common pitfalls in applying machine learning to each  ...  MACHINE LEARNING TECHNIQUES IN FINANCIAL RISK MANAGEMENT Machine Learning is a computational method that uses past information to improve performance in a specific task(s) or make accurate predictions  ... 
doi:10.1109/access.2020.3036322 fatcat:44z5jx3b2ff5xc6pcw3pwniyua

Deep Learning for Financial Applications : A Survey [article]

Ahmet Murat Ozbayoglu, Mehmet Ugur Gudelek, Omer Berat Sezer
2020 arXiv   pre-print
Meanwhile, within the Machine Learning (ML) field, Deep Learning (DL) started getting a lot of attention recently, mostly due to its outperformance over the classical models.  ...  Computational intelligence in finance has been a very popular topic for both academia and financial industry in the last few decades. Numerous studies have been published resulting in various models.  ...  Portfolio Management Portfolio Management is the process of choosing various assets within the portfolio for a predetermined period.  ... 
arXiv:2002.05786v1 fatcat:p4ykvxempzajpo66p2z6xaddp4

Deep Reinforcement Learning For Trading—A Critical Survey

Adrian Millea
2021 Data  
Deep reinforcement learning (DRL) has achieved significant results in many machine learning (ML) benchmarks.  ...  The market in focus for this survey is the cryptocurrency market; the results of this survey are two-fold: firstly, to find the most promising directions for further research and secondly, to show how  ...  Introduction Predicting and analysing financial indices has been of interest in the financial community for a long time, but recently, there has been a wide interest in the machine learning (ML) community  ... 
doi:10.3390/data6110119 fatcat:gwkzdl3mh5bg3noztt62zqd2be

A Survey of Machine Learning for IoT Networks

Dr. R. Thamaraiselvi, S. Anitha Selva Mary
2020 International journal of computer science and mobile computing  
Taxonomy of machine learning algorithms is introduced to illustrate how various methods are applied to the data in order to obtain higher level knowledge.  ...  This paper focuses on IoT network security aspects by exploring the serviceability of machine learning algorithms to identify anomalies in data from these networks.  ...  In spite of the recent wave of success in computer network learning, machine learning literature on its IoT services and systems implementations is scarce, and the purpose of this survey is to address  ... 
doi:10.47760/ijcsmc.2020.v09i10.006 fatcat:mipjab4sijdj3je2236kogcxkq

A Survey of Privacy Attacks in Machine Learning [article]

Maria Rigaki, Sebastian Garcia
2021 arXiv   pre-print
As machine learning becomes more widely used, the need to study its implications in security and privacy becomes more urgent.  ...  Our contribution in this research is an analysis of more than 40 papers related to privacy attacks against machine learning that have been published during the past seven years.  ...  THREAT MODEL In order to understand and defend against attacks to machine learning from a privacy perspective, it is useful to have a general model of the environment, the different actors, and the assets  ... 
arXiv:2007.07646v2 fatcat:sj7z2h2dhfdybgc234ha6hkrdq

A survey of big data and machine learning

Surender Reddy Salkuti
2020 International Journal of Electrical and Computer Engineering (IJECE)  
This paper presents a detailed analysis of big data and machine learning (ML) in the electrical power and energy sector.  ...  Finally, the challenges and opportunities of big data and machine learning are presented in this paper.  ...  2010 onwards a new field which is a subset of artificial intelligence (AI), and machine learning (ML) is the subset of AI, and deep learning is a subset of ML which started in early 2010.  ... 
doi:10.11591/ijece.v10i1.pp575-580 fatcat:sfj6p7gf3bdaxh4o4hwfxh7lmu

Model-Free Reinforcement Learning for Financial Portfolios: A Brief Survey [article]

Yoshiharu Sato
2019 arXiv   pre-print
Financial portfolio management is one of the problems that are most frequently encountered in the investment industry.  ...  In fact, the process of sequential computation of optimal component weights that maximize the portfolio's expected return subject to a certain risk budget can be reformulated as a discrete-time Markov  ...  loss in actual portfolio management.  ... 
arXiv:1904.04973v2 fatcat:u7ttwd4ykba67ijz7mjydnpzde

Deep Learning in Biometrics: A Survey

2019 Advances in Distributed Computing and Artificial Intelligence Journal  
In this survey, it is considered how the scientific advances in the field of deep learning are applied to biometrics in order to enhance the protection of our data.  ...  Firstly, a study will be conducted on tackling ocular identification of twins using deep learning.  ...  Finally, some conclusions will be brought up as well as a final review of what was done in this survey. But what is deep learning?  ... 
doi:10.14201/adcaij2019841932 fatcat:goenvskglzamdohj5yhahq2mzq

Machine Learning for Cultural Heritage: A Survey

Marco Fiorucci, Marina Khoroshiltseva, Massimiliano Pontil, Arianna Traviglia, Alessio Del Bue, Stuart James
2020 Pattern Recognition Letters  
The application of Machine Learning (ML) to Cultural Heritage (CH) has evolved since basic statistical approaches such as Linear Regression to complex Deep Learning models.  ...  We survey across ML and CH literature to identify the theoretical changes which contribute to the algorithm and in turn them suitable for CH applications.  ...  Supplementary material Supplementary material associated with this article can be found, in the online version, at doi: 10.1016/j.patrec.2020.02.017 .  ... 
doi:10.1016/j.patrec.2020.02.017 fatcat:smayxo3wcbfmhm33c6q4rnmr6i

Transfer Learning in Deep Reinforcement Learning: A Survey [article]

Zhuangdi Zhu, Kaixiang Lin, Anil K. Jain, Jiayu Zhou
2022 arXiv   pre-print
In this survey, we systematically investigate the recent progress of transfer learning approaches in the context of deep reinforcement learning.  ...  Reinforcement learning is a learning paradigm for solving sequential decision-making problems.  ...  Deep RL are also effective solutions to problems in Finance, including portfolio management [166, 167] , asset allocation [168] , and trading optimization [169] for improved power-delivery decisions  ... 
arXiv:2009.07888v5 fatcat:2rfeugb27ffv7jxh7siqn56s6e

A Survey on Machine Learning for Stock Price Prediction: Algorithms and Techniques

Mehtabhorn Obthong, Nongnuch Tantisantiwong, Watthanasak Jeamwatthanachai, Gary Wills
2020 Proceedings of the 2nd International Conference on Finance, Economics, Management and IT Business  
This paper reviews studies on machine learning techniques and algorithm employed to improve the accuracy of stock price prediction.  ...  Stock market trading is an activity in which investors need fast and accurate information to make effective decisions.  ...  INTRODUCTION In financial markets, a machine learning (ML) has become a powerful analytical tool used to help and manage investment efficiently.  ... 
doi:10.5220/0009340700630071 dblp:conf/femib/ObthongTJW20 fatcat:7mjgacqhhbggtiu7cfd7fhrs5y

Confidential machine learning on untrusted platforms: a survey

Sharma Sagar, Chen Keke
2021 Cybersecurity  
With a unified framework, we highlight the critical challenges and innovations in outsourcing machine learning confidentially.  ...  In this survey, we summarize notable studies in this emerging area of research.  ...  We organize the survey based on underlying design principles of CML rather than any specific machine learning problems.  ... 
doi:10.1186/s42400-021-00092-8 pmid:34805760 pmcid:PMC8591683 fatcat:vmdemrhszjcynp6rytvckg7o5i

Machine Learning for Quantitative Finance Applications: A Survey

Rundo, Trenta, di Stallo, Battiato
2019 Applied Sciences  
This paper proposes a review of some of the most significant works providing an exhaustive overview of recent machine learning (ML) techniques in the field of quantitative finance showing that these methods  ...  Despite their efficacy, the existing works face some drawbacks due to poor performance when managing a large amount of data with intrinsic complexity, high dimensionality and casual dynamicity.  ...  Reinforcement learning refers to a machine-learning paradigm which involves an "agent" in order to perform a task.  ... 
doi:10.3390/app9245574 fatcat:x5g2vrzovfcijlfjxmej4fo5nu
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