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Changlong Wu
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2020 – today
- 2024
- [c20]Jin Sima, Changlong Wu, Olgica Milenkovic, Wojciech Szpankowski:
Online Distribution Learning with Local Privacy Constraints. AISTATS 2024: 460-468 - [c19]Changlong Wu, Jin Sima, Wojciech Szpankowski:
Oracle-Efficient Hybrid Online Learning with Unknown Distribution. COLT 2024: 4992-5018 - [c18]Changlong Wu, Yifan Wang, Ananth Grama:
A Theory of Fault-Tolerant Learning. ICML 2024 - [c17]Michael Drmota, Philippe Jacquet, Changlong Wu, Wojciech Szpankowski:
Minimax Regret with Unbounded Weights. ISIT 2024: 2305-2310 - [c16]Xiaosong Huang, Hongyi Liu, Yifan Wu, Yujin Zhao, Changlong Wu, Songlin Zhang, Ling Jiang, Tong Jia, Ying Li, Zhonghai Wu:
OCRCL: Online Contrastive Learning for Root Cause Localization of Business Incidents. SANER 2024: 524-534 - [i8]Changlong Wu, Jin Sima, Wojciech Szpankowski:
Oracle-Efficient Hybrid Online Learning with Unknown Distribution. CoRR abs/2401.15520 (2024) - [i7]Jin Sima, Changlong Wu, Olgica Milenkovic, Wojciech Szpankowski:
Online Distribution Learning with Local Private Constraints. CoRR abs/2402.00315 (2024) - 2023
- [j2]Changlong Wu
, Mohsen Heidari
Regret Bounds for Log-Loss via Bayesian Algorithms. IEEE Trans. Inf. Theory 69(9): 5971-5989 (2023) - [j1]Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski:
Expected Worst Case Regret via Stochastic Sequential Covering. Trans. Mach. Learn. Res. 2023 (2023) - [c15]Changlong Wu, Ananth Grama, Wojciech Szpankowski:
Online Learning in Dynamically Changing Environments. COLT 2023: 325-358 - [c14]Changlong Wu, Yifan Wang, Ananth Grama, Wojciech Szpankowski:
Learning Functional Distributions with Private Labels. ICML 2023: 37728-37744 - [c13]Yujin Zhao, Ling Jiang, Ye Tao, Songlin Zhang, Changlong Wu, Yifan Wu, Tong Jia, Ying Li, Zhonghai Wu:
How to Manage Change-Induced Incidents? Lessons from the Study of Incident Life Cycle. ISSRE 2023: 264-274 - [c12]Yujin Zhao, Ling Jiang, Ye Tao, Songlin Zhang, Changlong Wu, Tong Jia, Xiaosong Huang, Ying Li, Zhonghai Wu:
Identifying Root-Cause Changes for User-Reported Incidents in Online Service Systems. ISSRE 2023: 287-297 - [i6]Changlong Wu, Ananth Grama, Wojciech Szpankowski:
Online Learning in Dynamically Changing Environments. CoRR abs/2302.00103 (2023) - [i5]Changlong Wu, Ananth Grama, Wojciech Szpankowski:
Robust Online Classification: From Estimation to Denoising. CoRR abs/2309.01698 (2023) - 2022
- [c11]Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski:
Sequential vs. Fixed Design Regrets in Online Learning. ISIT 2022: 438-443 - [c10]Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski:
Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm. NeurIPS 2022 - [i4]Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski:
Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm. CoRR abs/2205.03728 (2022) - [i3]Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski:
Expected Worst Case Regret via Stochastic Sequential Covering. CoRR abs/2209.04417 (2022) - 2021
- [c9]Changlong Wu, Narayana Santhanam:
Prediction with Finitely many Errors Almost Surely. AISTATS 2021: 3223-3231 - [c8]Changlong Wu, Narayana Santhanam:
Non-uniform Consistency of Online Learning with Random Sampling. ALT 2021: 1265-1285 - [c7]Changlong Wu, Narayana Santhanam:
Estimating Properties of Dynamic Graphical Models. ISIT 2021: 391-395 - 2020
- [c6]Changlong Wu, Narayana Prasad Santhanam:
Almost Uniform Sampling From Neural Networks. CISS 2020: 1-6 - [c5]Changlong Wu, Narayana Santhanam:
Entropy property testing with finitely many errors. ISIT 2020: 2568-2573
2010 – 2019
- 2019
- [c4]Changlong Wu, Narayana Santhanam:
Being correct eventually almost surely. ISIT 2019: 1989-1993 - [i2]Changlong Wu, Narayana Prasad Santhanam:
Almost Uniform Sampling From Neural Networks. CoRR abs/1912.04994 (2019) - 2018
- [c3]Changlong Wu, Wenxin Chen, June Zhang:
Greedy Algorithm with Approximation Ratio for Sampling Noisy Graph Signals. ICASSP 2018: 4654-4658 - [c2]Changlong Wu, Maryam Hosseini, Narayana Santhanam:
Redundancy of Unbounded Memory Markov Classes with Continuity Conditions. ISIT 2018: 211-215 - [i1]Changlong Wu, Maryam Hosseini, Narayana Santhanam:
Redundancy of unbounded memory Markov classes with continuity conditions. CoRR abs/1802.00136 (2018) - 2017
- [c1]Kevin Oshiro, Changlong Wu, Narayana P. Santhanam:
Jackknife estimation for Markov processes with no mixing constraints. ISIT 2017: 3020-3024
Coauthor Index
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