Approaches to Latency Management: Combining Hopby-Hop and End-to-End Networking
By Sebnem Ozer, Ph.D., Carl Klatsky, Dan Rice & John Chrostowski, Comcast
|
2020 |
Solving The Mysteries of the Distributed Access Architecture
By Matthew Stehman, Ramya Narayanaswamy, Jude Ferreira & Robert Gaydos, Comcast
|
2021 |
Accelerating the Virtualization: Introducing Hybrid Fiber Shelf into the Mix
By Venk Mutalik, Bob Gaydos, Dan Rice & Jorge Salinger, Comcast
|
2020 |
Intelligent Outside Plant Power Operations with Machine Learning
By Matthew Stehman, Comcast; Chris D’Andrea, Comcast; Ilana Weinstein, Comcast
|
2023 |
Machine Learning and Telemetry Improves Outside Plant Power Resiliency for More Reliable Networks
By Stephanie Ohnmacht, Matthew Stehman; Comcast
|
2022 |
Rapid and Automated Production Scale Activation of Expanded Upstream Bandwidth
By Rob Thompson, Rob Howald, John Chrostowski, Dan Rice, Amarildo Vieira, Rohini Vugumudi & Zhen Lu, Comcast Cable
|
2021 |
Applications of Machine Learning in Cable Access Networks
By Karthik Sundaresan, Nicolas Metts, Greg White, Albert Cabellos-Aparicio, CableLabs
|
2016 |
Operationalizing Streaming Telemetry and Machine Learning Model Serving: Customer Experience Automation
By Nick Pinckernell & Scott Rome, Comcast
|
2020 |
Profile Management Informed Proactive Network Maintenance
By Jason Rupe & Jingjie Zhu, CableLabs
|
2020 |
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 |
Scaling DAA: Smart, Continuous Network Health Monitoring for vCMTS with Machine Learning
By Ilana Weinstein, Comcast; Ramya Narayanaswamy, Comcast; Aaron Tomkins, Comcast; Nivedhitha Sridhar, Comcast
|
2023 |
Comcast Underground: Innovative Fiber Deployments Over Existing Underground Critical Infrastructure
By Venk Mutalik, Pat Wike, Doug Combs, Alan Gardiner, Dan Rice; Comcast
|
2022 |
Right Technician at the Right Time: Using Machine Learning to Predict Network Maintenance Issues
By Anastasia Vishnyakova, Rama Mahajanam, Mike O’Dell, May Merkle-Tan, Catherine Hay & Lisa Pham, Comcast Cable
|
2021 |
Modernizing Subscriber Management on the Road to 10G
By Sebnem Ozer, Ph.D., De Fu Li, Jason Combs, Bob Gaydos, Dan Rice; COMCAST
|
2022 |
DOCSIS 3.1 Profile Management Application and Algorithms
By Greg White and Karthik Sundaresan,
Cable Television Laboratories, Inc.
|
2016 |
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 |
DOCSIS 3.1 Multicast Profile Management Mechanism
By Yanbin Sun, Tao Ouyang, and Hesham ElBakoury,
Huawei Technologies Co.,Ltd.
|
2016 |
Optimizing Video Customer Experience with Machine Learning
By Mariela Fiorenzo, Claudio Righetti, María Cecilia Raggio, Fernando Ochoa & Gabriel Carro, Telecom Argentina S.A.
|
2019 |
An FPGA-based Coaxial Channel Emulator for Automated Testing and Validation
By Richard A Primerano, Comcast; Rick Spanbauer, Comcast
|
2023 |
Leveraging Machine Learning for Network Traffic Forecasting
By Diane Prisca Onguetou, PhD, Independent Consultant; Achintha Maddumabandara, Rogers Communications; Jeffrey Lee, Rogers Communications
|
2023 |
