Chen Wang

Orcid: 0000-0003-0204-2362

Affiliations:
  • IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA
  • Carnegie Mellon University, Department of Electrical and Computer Engineering, Pittsburgh, PA, USA (PhD 2017)


According to our database1, Chen Wang authored at least 27 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Õ(T<sup>-1</sup>) Convergence to (Coarse) Correlated Equilibria in Full-Information General-Sum Markov Games.
CoRR, 2024

Towards Pareto Optimal Throughput in Small Language Model Serving.
Proceedings of the 4th Workshop on Machine Learning and Systems, 2024

2023
Optimizing simultaneous autoscaling for serverless cloud computing.
CoRR, 2023

AWARE: Automate Workload Autoscaling with Reinforcement Learning in Production Cloud Systems.
Proceedings of the 2023 USENIX Annual Technical Conference, 2023

Acto: Automatic End-to-End Testing for Operation Correctness of Cloud System Management.
Proceedings of the 29th Symposium on Operating Systems Principles, 2023

Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Optimal Preemptive GPU Time-Sharing for Edge Model Serving.
Proceedings of the 9th International Workshop on Container Technologies and Container Clouds, 2023

2022
A Mean-Field Game Approach to Cloud Resource Management with Function Approximation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Reinforcement learning for resource management in multi-tenant serverless platforms.
Proceedings of the EuroMLSys '22: Proceedings of the 2nd European Workshop on Machine Learning and Systems, Rennes, France, April 5, 2022

Cloud-native workflow scheduling using a hybrid priority rule and dynamic task parallelism.
Proceedings of the 13th Symposium on Cloud Computing, SoCC 2022, 2022

SIMPPO: a scalable and incremental online learning framework for serverless resource management.
Proceedings of the 13th Symposium on Cloud Computing, SoCC 2022, 2022

2021
Is Function-as-a-Service a Good Fit for Latency-Critical Services?
Proceedings of the WoSC '21: Proceedings of the Seventh International Workshop on Serverless Computing (WoSC7) 2021, 2021

Theta-Scan: Leveraging Behavior-Driven Forecasting for Vertical Auto-Scaling in Container Cloud.
Proceedings of the 14th IEEE International Conference on Cloud Computing, 2021

2020
Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions.
Proceedings of the IMC '20: ACM Internet Measurement Conference, 2020

AI4DL: Mining Behaviors of Deep Learning Workloads for Resource Management.
Proceedings of the 12th USENIX Workshop on Hot Topics in Cloud Computing, 2020

Proactive Container Auto-scaling for Cloud Native Machine Learning Services.
Proceedings of the 13th IEEE International Conference on Cloud Computing, 2020

2019
Generating High-fidelity, Synthetic Time Series Datasets with DoppelGANger.
CoRR, 2019

AI Gauge: Runtime Estimation for Deep Learning in the Cloud.
Proceedings of the 31st International Symposium on Computer Architecture and High Performance Computing, 2019

FfDL: A Flexible Multi-tenant Deep Learning Platform.
Proceedings of the 20th International Middleware Conference, 2019

Touchdown on the Cloud: The Impact of the Super Bowl on Cloud.
Proceedings of the IEEE Fifth International Conference on Big Data Computing Service and Applications, 2019

2018
Resource Profile Advisor for Containers in Cognitive Platform.
Proceedings of the ACM Symposium on Cloud Computing, 2018

Comparing Cloud Content Delivery Networks for Adaptive Video Streaming.
Proceedings of the 11th IEEE International Conference on Cloud Computing, 2018

2017
QoE Based Management and Control for Large-Scale VoD System in the Cloud.
PhD thesis, 2017

Identifying Persistent and Recurrent QoE Anomalies for DASH Streaming in the Cloud.
Proceedings of the IEEE International Conference on Cloud Computing Technology and Science, 2017

2016
QWatch: Detecting and Locating QoE Anomaly for VoD in the Cloud.
Proceedings of the 2016 IEEE International Conference on Cloud Computing Technology and Science, 2016

2015
Users Know Better: A QoE Based Adaptive Control System for VoD in the Cloud.
Proceedings of the 2015 IEEE Global Communications Conference, 2015

QoE Driven Server Selection for VoD in the Cloud.
Proceedings of the 8th IEEE International Conference on Cloud Computing, 2015


  Loading...