Applications of Machine Learning in Cable Access Networks
By Karthik Sundaresan, Nicolas Metts, Greg White, Albert Cabellos-Aparicio, CableLabs
|
2016 |
Access Network Data Analytics
By Karthik Sundaresan & Jay Zhu, CableLabs
|
2017 |
Network Capacity and Machine Learning
By Dr. Claudio Righetti, Emilia Gibellini, Florencia De Arca, Carlos Germán Carreño Romano, Mariela Fiorenzo, Gabriel Carro & Fernando Rodrigo Ochoa, Cablevisión S.A.
|
2017 |
Can Future Networks Survive Without Artificial Intelligence?
By Dr. Claudio Righetti, Emilia Gibellini, Carlos Germán Carreño Romano & Gabriel Carro; Telecom Argentina S.A.
|
2019 |
Embracing Service Delivery Changes with Machine Learning
By Andrew Sundelin, Guavus, Inc.
|
2018 |
SDNized Cable Access Networks
By Karthik Sundaresan, CableLabs
|
2015 |
Low Latency DOCSIS: Overview And Performance Characteristics
By Greg White, Karthik Sundaresan & Bob Briscoe, CableLabs
|
2019 |
Machine Learning Applications in Cable TV Advertising: Usage and Challenges
By Srilal M Weerasinghe PhD, Charter Communications
|
2019 |
Accurately Estimating D3.1 Channel Capacity
By Karthik Sundaresan, CableLabs
|
2017 |
Simplifying Field Operations Using Machine Learning
By Sanjay Dorairaj, Bernard Burg & Nicholas Pinckernell, Comcast Corporation; Chris Bastian, SCTE
|
2017 |
A Machine Learning Pipeline for D3.1 Profile Management
By Maher Harb, Jude Ferreira, Dan Rice, Bryan Santangelo & Rick Spanbauer, Comcast
|
2019 |
Detecting Video Piracy with Machine Learning
By Matthew Tooley & Thomas Belford, NCTA – The Internet & Television Assocation
|
2019 |
DOCSIS 3.1 Profile Management Application and Algorithms
By Greg White and Karthik Sundaresan,
Cable Television Laboratories, Inc.
|
2016 |
Practical Lessons from D3.1 Deployments and a Profile Management Application
By Karthik Sundaresan, Jay Zhu & Mayank Mishra, CableLabs; James Lin, Kyrio/CableLabs
|
2019 |
An Overview Of TV White Space For The Cable Industry
By Tom du Breuil, Dave Gurney, Mark Kolber, Motorola, Inc.
|
2009 |
Machine Learning: The Past, Present and the Future
By Narayan Srinivasa, Intel Corporation
|
2016 |
FDX & D3.1 Capacity Scenarios
By Karthik Sundaresan, CableLabs
|
2018 |
Right-sizing Cable Modem Buffers For Maximum Application Performance
By Greg White, CableLabs and Richard Woundy, Yiu Lee, Carl Williams, Comcast
|
2011 |
Optimizing Video Customer Experience with Machine Learning
By Mariela Fiorenzo, Claudio Righetti, María Cecilia Raggio, Fernando Ochoa & Gabriel Carro, Telecom Argentina S.A.
|
2019 |
Toward Automated Intelligent Resource Optimization for vCMTS Using Machine Learning
By Kieran Mulqueen, Michael O’Hanlon, Marcin Spoczynski, Brendan Ryan, Thijs Metsch, Leonard Feehan & Ruth Quinn, Intel
|
2018 |
