Zhao Song

Orcid: 0000-0001-5263-7044

Affiliations:
  • Amazon AWS AI Labs, Santa Clara, CA, USA
  • Baidu Research, Sunnyvale, CA, USA (former)
  • Duke University, Department of Electrical and Computer Engineering, Durham, NC, USA (PhD 2018)


According to our database1, Zhao Song authored at least 12 papers between 2016 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
Vista: Machine Learning based Database Performance Troubleshooting Framework in Amazon RDS.
Proceedings of the 2024 ACM Symposium on Cloud Computing, 2024

2022
FITNESS: (Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers.
Proceedings of the International Conference on Machine Learning, 2022

2020
WaveFlow: A Compact Flow-based Model for Raw Audio.
Proceedings of the 37th International Conference on Machine Learning, 2020

Non-Autoregressive Neural Text-to-Speech.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Parallel Neural Text-to-Speech.
CoRR, 2019

Revisiting the Softmax Bellman Operator: New Benefits and New Perspective.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Learning Features for Unsupervised Learning and Reinforcement Learning.
PhD thesis, 2018

Revisiting the Softmax Bellman Operator: Theoretical Properties and Practical Benefits.
CoRR, 2018

2017
Scalable Model Selection for Belief Networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Linear Feature Encoding for Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Solving DEC-POMDPs by Expectation Maximization of Value Function.
Proceedings of the 2016 AAAI Spring Symposia, 2016


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