Embracing Service Delivery Changes with Machine Learning
By Andrew Sundelin, Guavus, Inc.
|
2018 |
Leveraging Machine Intelligence and Operations Analytics
By Andrew Sundelin, Guavus
|
2017 |
Predicting Service Impairments from Set-top Box Errors in Near Real-Time and What to Do About It
By Justin Watson, Comcast; Roger Brooks, Andrew Colby, Pankaj Kumar, Anant Malhotra & Mudit Jain, Guavus, Inc.
|
2018 |
Applications of Machine Learning in Cable Access Networks
By Karthik Sundaresan, Nicolas Metts, Greg White, Albert Cabellos-Aparicio, CableLabs
|
2016 |
Create Data-Driven Solutions to Optimize IP Content Delivery and Identify Revenue Opportunities
By Brennen Lynch and Anukool Lakhina, Guavus, Inc.
|
2014 |
Using Machine Learning to Automate Node Split Designs and HFC Augmentation Options
By Keith R. Hayes, IMMCO, Inc.
|
2020 |
Multi Layered Unsupervised Machine Learning for Detection of Real Time Network Service Impairment
By Eric Frishman, Comcast; Devangna Kaushish, Comcast; Russell Harlin, Comcast; Aditya Vallabhajosyula, Comcast; Eswaramoorthy Subramaniam, Comcast
|
2023 |
Applications Of Big Data Analytics To Identify New Revenue Streams & Improve Customer Experience
By Anukool Lakhina and Brennen Lynch, Guavus, Inc.
|
2013 |
Customer First: CX-Driven Augmented Operations
By Roger Brooks, Ph.D., Pankaj Kumar, Mudit Jain, Megha Vij, Nandit Jain & Andrew Colby, Guavus
|
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 |
Detecting Video Piracy with Machine Learning
By Matthew Tooley & Thomas Belford, NCTA – The Internet & Television Assocation
|
2019 |
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 |
Simplifying Field Operations Using Machine Learning
By Sanjay Dorairaj, Bernard Burg & Nicholas Pinckernell, Comcast Corporation; Chris Bastian, SCTE
|
2017 |
Machine Learning: The Past, Present and the Future
By Narayan Srinivasa, Intel Corporation
|
2016 |
Implement Closed-Loop Network Decisioning Now with Big Data Analytics and Fuel Future-State SDN Use Cases Through a Common Platform Deployment
By Brennen Lynch and Anukool Lakhina, Guavus, Inc.
|
2014 |
A Machine Learning Pipeline for D3.1 Profile Management
By Maher Harb, Jude Ferreira, Dan Rice, Bryan Santangelo & Rick Spanbauer, Comcast
|
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 |
The Big Network Changes Coming with 1+ Gbps Service Environments of the Future
By Tom Cloonan, Tushar Mathur, Ruth Cloonan, Ben Widrevitz & John Ulm, ARRIS
|
2017 |
Encourage EVERY Employee to Learn and Utilize Data, Analytics, and Machine Learning (DAML)
By Robert Gray Wald, MS, SCTE® a subsidiary of CableLabs®
|
2022 |
Optimizing Video Customer Experience with Machine Learning
By Mariela Fiorenzo, Claudio Righetti, María Cecilia Raggio, Fernando Ochoa & Gabriel Carro, Telecom Argentina S.A.
|
2019 |
