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Meta-Reinforcement Learning via Buffering Graph Signatures for Live Video Streaming Events [article]

Stefanos Antaris, Dimitrios Rafailidis, Sarunas Girdzijauskas
2021 arXiv   pre-print
In this study, we present a meta-learning model to adapt the predictions of the network's capacity between viewers who participate in a live video streaming event.  ...  To combat this issue, we design a graph signature buffer to calculate the structural similarities of several streaming events and adjust the training of the global model accordingly.  ...  Extracting knowledge from live video streaming events is defined as the following meta-RL process: Meta-RL in Live Video Streaming Events In meta-RL for live video streaming events, we consider a distribution  ... 
arXiv:2111.09412v1 fatcat:3mml2xxlrrconkowa4kkvncoee

Table of contents

2021 ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
VOICE ACTIVITY ...................................... 4165 DETECTION IN LIVE MUSICAL VIDEO STREAMS Yuanbo Hou, Ghent University, Belgium; Yi Deng, New York University, United States; Bilei Zhu, Zejun  ...  26.2: TEMPORAL LINK PREDICTION VIA REINFORCEMENT LEARNING ......................................... 3460 Ye Tao, Ying Li, Zhonghai Wu, Peking University, China MLSP-26.4: A DEEP REINFORCEMENT LEARNING  ... 
doi:10.1109/icassp39728.2021.9414617 fatcat:m5ugnnuk7nacbd6jr6gv2lsfby

Inductive Biases for Deep Learning of Higher-Level Cognition [article]

Anirudh Goyal, Yoshua Bengio
2021 arXiv   pre-print
This hypothesis would suggest that studying the kind of inductive biases that humans and animals exploit could help both clarify these principles and provide inspiration for AI research and neuroscience  ...  Deep learning already exploits several key inductive biases, and this work considers a larger list, focusing on those which concern mostly higher-level and sequential conscious processing.  ...  We want efficient large scale learning, e.g., brought by variants of stochastic gradient descent and end-to-end learning behind the state-of-the-art in modern deep learning.  ... 
arXiv:2011.15091v3 fatcat:pc6cdt7srbdqhigb6dzskbq6sm

A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

Raouf Boutaba, Mohammad A. Salahuddin, Noura Limam, Sara Ayoubi, Nashid Shahriar, Felipe Estrada-Solano, Oscar M. Caicedo
2018 Journal of Internet Services and Applications  
There are various surveys on ML for specific areas in networking or for specific network technologies.  ...  Machine Learning (ML) has been enjoying an unprecedented surge in applications that solve problems and enable automation in diverse domains.  ...  Acknowledgments We thank the anonymous reviewers for their insightful comments and suggestions that helped us improve the quality of the paper.  ... 
doi:10.1186/s13174-018-0087-2 fatcat:jvwpewceevev3n4keoswqlcacu

Crawler [chapter]

Kenneth A. Ross, Christian S. Jensen, Richard Snodgrass, Curtis E. Dyreson, Christian S. Jensen, Richard Snodgrass, Spiros Skiadopoulos, Cristina Sirangelo, Mary Lynette Larsgaard, Gösta Grahne, Daniel Kifer, Hans-Arno Jacobsen (+106 others)
2009 Encyclopedia of Database Systems  
As a result, it is common (at the time of writing) for data accesses to RAM to require several hundred CPU cycles to resolve.  ...  For such workloads, improving the locality of data-intensive operations can have a direct impact on the system's overall performance.  ...  Skinner's experimental analyses of animal behavior using reinforcement learning [2] .  ... 
doi:10.1007/978-0-387-39940-9_2315 fatcat:x4qspjdytvhvroc7h753dihp7u

A Survey on Adversarial Attacks for Malware Analysis [article]

Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam
2022 arXiv   pre-print
Increasing dependency on data has paved the blueprint for ever-high incentives to camouflage machine learning models.  ...  The evolution of machine learning from traditional algorithms to modern deep learning architectures has shaped the way today's technology functions.  ...  Reinforcement Learning Reinforcement learning can be viewed both as a learning problem and a sub-field of machine learning [77] .  ... 
arXiv:2111.08223v2 fatcat:fiw3pgunsvb2vo7uv72mp6b65a

Access Control [chapter]

Anne Canteaut, Gerald Brose, Hakki C. Cankaya, Hakki C. Cankaya, Aaron Estes, Sabrina De Capitani di Vimercati, Sabrina De Capitani di Vimercati, Davide Martinenghi, Yvo Desmedt, Marijke De Soete, Alex Biryukov, Alex Biryukov (+36 others)
2011 Encyclopedia of Cryptography and Security  
Examples include mailing lists, chat programs, streaming audio, streaming video, and Web pages.  ...  a bit-stream.  ...  Web Conference A meeting of participants from disparate geographic locations that's held in a virtual environment on the World Wide Web, with communication taking place via text, audio, video, or a combination  ... 
doi:10.1007/978-1-4419-5906-5_179 fatcat:ibx7eeeyfrgmlfjprx3cnfuvkq

2020 Index IEEE Transactions on Vehicular Technology Vol. 69

2020 IEEE Transactions on Vehicular Technology  
+ Check author entry for coauthors ami-mFading Channels With Integer and Non-Integerm; TVT March 2020 2785-2801 Hoang, T.M., Tran, X.N., Nguyen, B.C., and Dung, L.T., On the Performance of MIMO Full-Duplex  ...  H., TVT Feb. 2020 1766-1776 Jiang, C., see Yao, H., TVT June 2020 6718-6730 Jiao, L., see Ju, H., TVT Dec. 2020 15325-15334 Jiao, Y., Wang, P., Niyato, D., Lin, B., and Kim, D.I., Mechanism Design for  ...  ., +, TVT April 2020 3760-3772 Buffer storage A Hierarchical Buffer Management Approach to Rate Adaptation for 360-Degree Video Streaming.  ... 
doi:10.1109/tvt.2021.3055470 fatcat:536l4pgnufhixneoa3a3dibdma

Key Event Receipt Infrastructure (KERI) [article]

Samuel M. Smith
2021 arXiv   pre-print
In the direct mode, the identity controller establishes control via verified signatures of the controlling key-pair.  ...  The indirect mode extends that trust basis with witnessed key event receipt logs (KERLs) for validating events.  ...  Because transitive trust facilitates the transfer of other types of value, a portable decentralized identity meta-system e.g. and autonomic identity system enables an identity meta-platform for commerce  ... 
arXiv:1907.02143v15 fatcat:tiwosgty6fe4rl3z46of3z5pji

MAC-REALM: A Video Content Feature Extraction and Modelling Framework

Minaz Parmar, Marios C. Angelides
2015 Computer journal  
To be able to search the video in a content based manner, the content features of the video need to be extracted and modelled into a content model, which can then act as a searchable proxy for the video  ...  Traditional text based search engines are no longer optimal for searching, as they cannot provide a granular search of the content inside video footage.  ...  This naming convention for scenes, shots and objects is then used as the input for the Semantics DS relations structure, via the Graph DS.  ... 
doi:10.1093/comjnl/bxv042 fatcat:hyedqykm75ey5nxdmbzdwkrvoa

Unsupervised human activity analysis for intelligent mobile robots

Paul Duckworth, David C. Hogg, Anthony G. Cohn
2019 Artificial Intelligence  
Our presented framework models each extended observation as a probabilistic mixture over the learned activities, meaning it can learn human activity models even when embedded in continuous video sequences  ...  This allows the mobile robot to efficiently learn and update its models of human activity over time, discarding the raw data, allowing for life-long learning.  ...  simple activities for daily living from a static camera dataset [Tayyub et al., 2015] ; and even perform reasoning about spatio-temporal events being observed [Dubba et al., 2011] .  ... 
doi:10.1016/j.artint.2018.12.005 fatcat:vq56rrsuojfq3kzr3ip3tj4d74

The Psychophysiology Primer: A Guide to Methods and a Broad Review with a Focus on Human–Computer Interaction

Benjamin Cowley, Marco Filetti, Kristian Lukander, Jari Torniainen, Andreas Henelius, Lauri Ahonen, Oswald Barral, Ilkka Kosunen, Teppo Valtonen, Minna Huotilainen, Niklas Ravaja, Giulio Jacucci
2016 Foundations and Trends® in Human–Computer Interaction  
Acknowledgments The work was supported in part by the Finnish Funding Agency for Innovation (project Re:Know, No. 5159/31/2014).  ...  Stream processing systems are often represented as directed graphs comprising the three above-mentioned components.  ...  Event-related brain potentials Event-related brain potentials are well-known and widely studied signatures of brain activity that are time-locked to a specific stimulus event, such as the beginning of  ... 
doi:10.1561/1100000065 fatcat:2hpkqxxtyfg5nhb3canmxg6shy

Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment [article]

Jithin Jagannath, Anu Jagannath, Sean Furman, Tyler Gwin
2020 arXiv   pre-print
Then we discuss how reinforcement learning is explored for using this information to provide autonomous control and navigation for UAS.  ...  We then provide an overview of some of the key deep learning and reinforcement learning techniques discussed throughout this chapter.  ...  Reinforcement Learning for UAS Autonomy Reinforcement learning provides a learning framework allowing agents to act optimally via sequential interactions with its environment.  ... 
arXiv:2009.03349v2 fatcat:5ylreoukrfcrtorzzp44mntjum

Deep Neural Mobile Networking [article]

Chaoyun Zhang
2020 arXiv   pre-print
This makes monitoring and managing the multitude of network elements intractable with existing tools and impractical for traditional machine learning algorithms that rely on hand-crafted feature engineering  ...  In particular, deep learning based solutions can automatically extract features from raw data, without human expertise.  ...  Strong service differentiation needs are already emerging in current deployments, where, e.g., live video streaming must coexist with on-line gaming or shared cloud services.  ... 
arXiv:2011.05267v1 fatcat:yz2zp5hplzfy7h5kptmho7mbhe

2019 Index IEEE Systems Journal Vol. 13

2019 IEEE Systems Journal  
., +, JSYST June 2019 1526-1533 Online Data Stream Analytics for Dynamic Environments Using Self-Regularized Learning Framework.  ...  Ferdowsi, M., +, JSYST Dec. 2019 4260-4268 Online Data Stream Analytics for Dynamic Environments Using Self-Regu- larized Learning Framework.  ... 
doi:10.1109/jsyst.2020.2965224 fatcat:x7hx4luelzforfuzigmwmfyhgm
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