Machine Learning: The Past, Present and the Future
By Narayan Srinivasa, Intel Corporation
|
2016 |
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 |
Simplifying Field Operations Using Machine Learning
By Sanjay Dorairaj, Bernard Burg & Nicholas Pinckernell, Comcast Corporation; Chris Bastian, SCTE
|
2017 |
Applications of Machine Learning in Cable Access Networks
By Karthik Sundaresan, Nicolas Metts, Greg White, Albert Cabellos-Aparicio, CableLabs
|
2016 |
Intel’s Vision Of Sports Immersion
By Guy Blair and Rajeeb Hazra, Intel Corporation - Intel Architecture Labs
|
2000 |
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 |
Detecting Video Piracy with Machine Learning
By Matthew Tooley & Thomas Belford, NCTA – The Internet & Television Assocation
|
2019 |
Optimizing Video Customer Experience with Machine Learning
By Mariela Fiorenzo, Claudio Righetti, María Cecilia Raggio, Fernando Ochoa & Gabriel Carro, Telecom Argentina S.A.
|
2019 |
A Machine Learning Pipeline for D3.1 Profile Management
By Maher Harb, Jude Ferreira, Dan Rice, Bryan Santangelo & Rick Spanbauer, Comcast
|
2019 |
Leveraging Machine Learning for Network Traffic Forecasting
By Diane Prisca Onguetou, PhD, Independent Consultant; Achintha Maddumabandara, Rogers Communications; Jeffrey Lee, Rogers Communications
|
2023 |
Machine Learning Applications in Cable TV Advertising: Usage and Challenges
By Srilal M Weerasinghe PhD, Charter Communications
|
2019 |
Best Practices for A/B Testing Machine Learning Models
By Piper Williams, Charter Communications; Ryan Lewis, Charter Communications; Miranda Kroehl, Charter Communications; Veronica Bloom, Charter Communications; Brock Bose, Charter Communications
|
2023 |
Operational Transformation Via Machine Learning
By Shamil Assylbekov, PhD. & Devin Levy, Charter Communications
|
2018 |
Machine Learning and Proactive Network Maintenance: Transforming Today's Plant Operations
By Brady Volpe, The VolpeFirm and NimbleThis; Berk Ottlik, NimbleThis LLC
|
2021 |
Machine Learning and Telemetry Improves Outside Plant Power Resiliency for More Reliable Networks
By Stephanie Ohnmacht, Matthew Stehman; Comcast
|
2022 |
Embracing Service Delivery Changes with Machine Learning
By Andrew Sundelin, Guavus, Inc.
|
2018 |
Using Machine Learning to Automate Node Split Designs and HFC Augmentation Options
By Keith R. Hayes, IMMCO, Inc.
|
2020 |
Time Teletext - Present And Future
By Pedro Barros, Barros & Associates Ltd. & John Lopinto, Time Video Information Services Inc.
|
1983 |
Encourage EVERY Employee to Learn and Utilize Data, Analytics, and Machine Learning (DAML)
By Robert Gray Wald, MS, SCTE® a subsidiary of CableLabs®
|
2022 |
Machine Learning Model for Customer Claim Prediction in HFC Subscribers
By Dr. Claudio Righetti, Telecom Argentina S.A.; Matilde Cuenca, Telecom Argentina S.A.; Dr. Diego Martinez Heimann, Telecom Argentina S.A.
|
2023 |
