Changlong Wu

According to our database, Changlong Wu authored at least 20 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Online Distribution Learning with Local Private Constraints.

Jin Sima, Changlong Wu, Olgica Milenkovic, Wojciech Szpankowski

CoRR, 2024

Oracle-Efficient Hybrid Online Learning with Unknown Distribution.

Changlong Wu, Jin Sima, Wojciech Szpankowski

CoRR, 2024

2023

Regret Bounds for Log-Loss via Bayesian Algorithms.

Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski

IEEE Trans. Inf. Theory, September, 2023

Robust Online Classification: From Estimation to Denoising.

Changlong Wu, Ananth Grama, Wojciech Szpankowski

CoRR, 2023

How to Manage Change-Induced Incidents? Lessons from the Study of Incident Life Cycle.

Yujin Zhao, Ling Jiang, Ye Tao, Songlin Zhang, Changlong Wu, Yifan Wu, Tong Jia, Ying Li, Zhonghai Wu

Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering, 2023

Identifying Root-Cause Changes for User-Reported Incidents in Online Service Systems.

Yujin Zhao, Ling Jiang, Ye Tao, Songlin Zhang, Changlong Wu, Tong Jia, Xiaosong Huang, Ying Li, Zhonghai Wu

Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering, 2023

Learning Functional Distributions with Private Labels.

Changlong Wu, Yifan Wang, Ananth Grama, Wojciech Szpankowski

Proceedings of the International Conference on Machine Learning, 2023

Online Learning in Dynamically Changing Environments.

Changlong Wu, Ananth Grama, Wojciech Szpankowski

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Expected Worst Case Regret via Stochastic Sequential Covering.

Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski

CoRR, 2022

Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm.

Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sequential vs. Fixed Design Regrets in Online Learning.

Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski

Proceedings of the IEEE International Symposium on Information Theory, 2022

2021

Estimating Properties of Dynamic Graphical Models.

Changlong Wu, Narayana Santhanam

Proceedings of the IEEE International Symposium on Information Theory, 2021

Non-uniform Consistency of Online Learning with Random Sampling.

Changlong Wu, Narayana Santhanam

Proceedings of the Algorithmic Learning Theory, 2021

Prediction with Finitely many Errors Almost Surely.

Changlong Wu, Narayana Santhanam

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Entropy property testing with finitely many errors.

Changlong Wu, Narayana Santhanam

Proceedings of the IEEE International Symposium on Information Theory, 2020

Almost Uniform Sampling From Neural Networks.

Changlong Wu, Narayana Prasad Santhanam

Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020

2019

Being correct eventually almost surely.

Changlong Wu, Narayana Santhanam

Proceedings of the IEEE International Symposium on Information Theory, 2019

2018

Redundancy of Unbounded Memory Markov Classes with Continuity Conditions.

Changlong Wu, Maryam Hosseini, Narayana Santhanam

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Greedy Algorithm with Approximation Ratio for Sampling Noisy Graph Signals.

Changlong Wu, Wenxin Chen, June Zhang

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Jackknife estimation for Markov processes with no mixing constraints.

Kevin Oshiro, Changlong Wu, Narayana P. Santhanam

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017