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Learning and Communicating the Latent States of Human-Machine Collaboration

Vaibhav V. Unhelkar, Julie A. Shah
2018 Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence  
Thus, the objective of this thesis research is to develop novel algorithms that enable artificial agents to learn and reason about the latent states of human-machine collaboration and achieve fluent interaction  ...  ., the state transition function) and even specifying the features (i.e., the relevant states) of human-machine collaboration is difficult.  ...  Hence, our solutions leverage communication between human and artificial agents for effective learning and utilization of the latent states of human-machine collaboration.  ... 
doi:10.24963/ijcai.2018/838 dblp:conf/ijcai/UnhelkarS18 fatcat:thes727oofapbasms5q5haeh2u

An Abstract State Machine (ASM) Representation of Learning Process in FLOSS Communities [chapter]

Patrick Mukala, Antonio Cerone, Franco Turini
2015 Lecture Notes in Computer Science  
In this paper, we describe the adoption of Abstract States Machines (ASMs) as a specification methodology for the description of learning processes in FLOSS.  ...  Free/Libre Open Source Software (FLOSS) communities as collaborative environments enable the occurrence of learning between participants in these groups.  ...  Abstract State Machines (ASMs) for Learning Processes in FLOSS Communities Modeling learning processes through ASMs grew out of a need to express the flow of occurrence for processes.  ... 
doi:10.1007/978-3-319-15201-1_15 fatcat:bpehcax2efckjobyxowdfvtkum

Machine learned features from density of states for accurate adsorption energy prediction

Victor Fung, Guoxiang Hu, P. Ganesh, Bobby G. Sumpter
2021 Nature Communications  
Here, we demonstrate an approach to predict energies using a convolutional neural network-based machine learning model to automatically obtain key features from the electronic density of states (DOS).  ...  However, in recent years, more involved machine learning (ML) methods have become an appealing alternative to provide predictions especially where multiple features or nonlinear relationships are involved  ...  antibonding states.  ... 
doi:10.1038/s41467-020-20342-6 pmid:33398014 fatcat:k4ilomhkj5ek3dlv2iolwssj3i

Machine learning based energy-free structure predictions of molecules, transition states, and solids

Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld
2021 Nature Communications  
learning models.  ...  Exploiting implicit correlations among relaxed structures in training data sets, our machine learning model Graph-To-Structure (G2S) generalizes across compound space in order to infer interatomic distances  ...  The analysis of machine learning predictions is crucial in order to better understand the G2S model.  ... 
doi:10.1038/s41467-021-24525-7 fatcat:32cp2j4k7ved7ivhc2o7tmiz2i

Identification of Bugs and Vulnerabilities in TLS Implementation for Windows Operating System Using State Machine Learning [chapter]

Tarun Yadav, Koustav Sadhukhan
2019 Communications in Computer and Information Science  
We have used protocol state fuzzing to identify vulnerable and undesired state transitions in the state machine of the protocol for various versions of SChannel.  ...  In this paper, we analyze state machine models of TLS protocol implementation of SChannel library and describe weaknesses and design flaws in these models, found using protocol state fuzzing.  ...  LEARNING OF TLS PROTOCOL STATE MACHINE State Machine of a system indicates the system behavior for every kind of inputs to the system.  ... 
doi:10.1007/978-981-13-5826-5_27 fatcat:rd33xjs7jzam3mcbjx5sq2anl4

Role of Machine Learning and Data Mining in Internet Security: Standing State with Future Directions

Bilal Ahmad, Wang Jian, Zain Anwar Ali
2018 Journal of Computer Networks and Communications  
This study highlights the developing research about the application of machine learning and data mining in Internet security.  ...  Communications and networks are highly vulnerable to threats because of increase in hacking.  ...  Conclusion is study demonstrates the literature survey-based on machine learning/data mining techniques for Internet/communication security. e study highlighted the papers that define the use of multiple  ... 
doi:10.1155/2018/6383145 fatcat:cm7ncpbgdja2nlvbooddp5tgb4

Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future

Syed Junaid Nawaz, Shree K. Sharma, Shurjeel Wyne, Mohammad N. Patwary, Md Asaduzzaman
2019 IEEE Access  
MACHINE LEARNING FOR B5G NETWORKS ML is a subbranch of Artificial Intelligence (AI) in which machines learn, perform, and improve their operations by exploiting the operational knowledge and experience  ...  FUNDAMENTALS OF QUANTUM MACHINE LEARNING This section revisits the ML methods discussed in Sec.  ... 
doi:10.1109/access.2019.2909490 fatcat:27eqrqfadfcnfmultqjnykweai

Analysis of Manufacturing Process Sequences, Using Machine Learning on Intermediate Product States (as Process Proxy Data) [chapter]

Thorsten Wuest, Christopher Irgens, Klaus-Dieter Thoben
2013 IFIP Advances in Information and Communication Technology  
After showing that a in detail description based on cause-effect models is not economical viable today, the possibilities of using machine learning on intermediate product states to analyze the process  ...  Providing a chance to analyze large amounts of data with high dimensionality and complexity, machine learning tools combined with cluster analysis are perfectly suited for the task at hand within the product  ...  The perspective on the product by its time-dependent state over the manufacturing process corresponds directly with the requirements of machine learning tools.  ... 
doi:10.1007/978-3-642-40361-3_1 fatcat:uj3iavmerbgz5fabnxbezqeloi

Towards Effective Classification of aMCI Based on Resting-State Multiscale Brain Features and Machine Learning Approaches

Chunting Cai, Jiqiang Yan, Yu Zhou, Wuyang Zheng, Chenhui Yang, Zhemin Zhang, Bokui Chen, Dan Hong, Yuanpeng Zhang
2021 Wireless Communications and Mobile Computing  
Support vector machine based on radial basis function (RBF-SVM) for small data learning is adopted to evaluate the effectiveness of the proposed features.  ...  Nevertheless, intelligent diagnosis analysis is still confronted with the issue that it is challenging to extract effective features from the limited and high-dimensional data, particularly in resting-state  ...  With the rapid development of machine learning technology, feature extraction and classification algorithms related to disease have become a hot spot.  ... 
doi:10.1155/2021/9975237 fatcat:gof3eztcxfe4nepw3bzatonhbm

The Multi-Level Data Exchange with Representational State Transfer on Service-Oriented Architecture

Worrapong Nuam-In, Division of Information and Communication Technology for Education, Faculty of Technical Education, King Mongkut's University of Technology North Bangkok (KMUTNB), Bangkok, Thailand, Prachyanun Nilsook, Panita Wannapiroon
2020 International Journal of Machine Learning and Computing  
Index Terms-Data exchange, representational state transfer, REST, service-oriented architecture, SOA.  ...  JavaScript Object Notation (JSON) can transfer the data in the form of the minimization International Journal of Machine Learning and Computing, Vol. 10, No. 1, January 2020 data exchange.  ...  Data Exchange & Communication Protocol This study uses the Representational State Transfer (REST) style because it is simple and easy to use.  ... 
doi:10.18178/ijmlc.2020.10.1.895 fatcat:clx46ctgxvbg7jrk6nbgz2jzsu

Preface to the special issue on analysis in machine learning and data science

Andreas Chirstmann, ,Department of Mathematics Stochastics University of Bayreuth 95440 Bayreuth, Germany, Qiang Wu, Ding-Xuan Zhou, ,Department of Mathematical Sciences Middle Tennessee State University Murfreesboro, TN 37132, USA, ,School of Data Science and Department of Mathematics City University of Hong Kong 83 Tat Chee Avenue, Kowloon Hong Kong, China
2020 Communications on Pure and Applied Analysis  
Nine papers are devoted to analysis in machine learning, which characterizes computational and theoretical properties of machine learning algorithms by mathematical tools developed from optimization, convex  ...  There are eighteen papers in this special issue, covering a variety of topics in machine learning and data science.  ... 
doi:10.3934/cpaa.2020171 fatcat:tu3hfj2rvrgl7ih65dzae5i2xe

Introduction to the JOCN Special Issue on Machine Learning and Data Analytics for Optical Communications and Networking

Massimo Tornatore, Martin Birk, Alan Pak Tao Lau, Qiong Zhang, Darko Zibar
2018 Journal of Optical Communications and Networking  
We provide a brief overview of the current state of machine learning in optical networks, followed by a categorization of the eleven papers in this special issue.  ...  Traffic Matrix Prediction and Optical Path Performance Prediction"), and on anomaly detection in the optical layer ("Using Machine Learning in Communication Networks").  ... 
doi:10.1364/jocn.10.000ml1 fatcat:gj7j57shtrexhldeebxxlg5a7m

Compressed Sensing Based on Tensor Network Machine Learning

Shao Ming Fei
2021 Physical Science & Biophysics Journal  
We introduce the scheme of compressed sensing based on tensor-network machine learning, which enables to compress and communicate information through the generative tensor-network states.  ...  The state Ψ is first obtained by unsupervised learning of tensor network, which characterizes the set of training images.  ...  The idea of compressed sensing based on tensornetwork machine learning is to encode and communicate the Shao-Ming Fei. Compressed Sensing Based on Tensor Network Machine Learning.  ... 
doi:10.23880/psbj-16000174 fatcat:pzlstpg75fb5bcbwqcpjhttbpe

2020 Index IEEE Communications Surveys&Tutorials Vol. 22

2020 IEEE Communications Surveys and Tutorials  
., +, COMST Secondquarter 2020 1251-1275 NOMA-Assisted Machine-Type Communications in UDN: State-of-the-Art and Challenges.  ...  Shahab, M.B., +, COMST Thirdquarter 2020 1805-1838 NOMA-Assisted Machine-Type Communications in UDN: State-of-the-Art and Challenges.  ... 
doi:10.1109/comst.2020.3040097 fatcat:pyg6ap7huvaw7a72khurr4oh7y

Journal of Selected Topics in Quantum Electronics on Machine Learning in Photonic Communication and Measurement Systems

2021 IEEE Journal of Selected Topics in Quantum Electronics  
The IEEE Journal of Selected Topics in Quantum Electronics (JSTQE) invites manuscript submissions in Machine Learning for Photonic Communication and Measurements Systems.  ...  Introducing intelligence as well using machine learning to design the next generation of components and systems as well as measurement systems is an emerging line of research in the photonics community  ...  The IEEE Journal of Selected Topics in Quantum Electronics (JSTQE) invites manuscript submissions in Machine Learning for Photonic Communication and Measurements Systems.  ... 
doi:10.1109/jstqe.2021.3067418 fatcat:saxjr3vy7bh6tpsdxctftlxeey
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