Zhao Song

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 11 papers between 2016 and 2022.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Book

In proceedings

Article

PhD thesis

Dataset

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Links

On csauthors.net:

Bibliography

2022

FITNESS: (Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers.

[BibT_eX]

[DOI]

Abishek Sankararaman

Balakrishnan Narayanaswamy

Vikramank Y. Singh

Zhao Song

Proceedings of the International Conference on Machine Learning, 2022

2020

WaveFlow: A Compact Flow-based Model for Raw Audio.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Non-Autoregressive Neural Text-to-Speech.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Parallel Neural Text-to-Speech.

[BibT_eX]

[DOI]

CoRR, 2019

Revisiting the Softmax Bellman Operator: New Benefits and New Perspective.

[BibT_eX]

[DOI]

Zhao Song

Ronald Parr

Lawrence Carin

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Learning Features for Unsupervised Learning and Reinforcement Learning.

[BibT_eX]

[DOI]

Zhao Song

PhD thesis, 2018

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

[BibT_eX]

[DOI]

Zhao Song

Ronald E. Parr

Lawrence Carin

CoRR, 2018

2017

Scalable Model Selection for Belief Networks.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Solving DEC-POMDPs by Expectation Maximization of Value Function.

[BibT_eX]

[DOI]

Zhao Song

Xuejun Liao

Lawrence Carin

Proceedings of the 2016 AAAI Spring Symposia, 2016

Zhao Song

Timeline

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Links

On csauthors.net:

Bibliography

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