Publications

Publications

Google Scholar Profile

Preprints

  1. Y. Bu*, G. Aminian*, L. Toni, M. R. D. Rodrigues, G. W. Wornell. “An Exact Characterization of the Generalization Error for the Gibbs Algorithm,” (* equal contribution), submitted to IEEE Transactions on Information Theory, preliminary version appeared in NeurIPS 2021.
  2. A. Weiss, A. Lancho, Y. Bu, G. W. Wornell. “A Bilateral Bound on the Mean Squared Error for Estimation in Model Mismatch,” submitted to IEEE Signal Processing Letter, Jul 2022.
  3. M. Shen, Y. Bu, P. Sattigeri, S. Ghosh, S. Das, G. W. Wornell. “Post-hoc Uncertainty Learning using a Dirichlet Meta-Model,” submitted to Conference on Neural Information Processing Systems (NeurIPS 2022), May 2022. 
  4. M. Shen, Y. Bu, G. W. Wornell. “On the Benefits of Selectivity in Pseudo-Labeling for Unsupervised Multi-Source-Free Domain Adaptation,” submitted to Conference on Neural Information Processing Systems (NeurIPS 2022), May 2022. 
  5. Y. Bu, J. Lu, V. V. Veeravalli. “Active and Adaptive Sequential learning,” arXiv preprint, 2020. 

Journal Publications

  1. Y. Bu*, J. K. Lee*, P. Sattigeri, R. Panda, G. W. Wornell, L. Karlinsky, R. Feris. “A Maximal Correlation Framework for Fair Machine Learning,” (* equal contribution), Entropy 24, no. 4, pp. 461, Mar. 2022.
  2. Y. Bu, W. Gao, S. Zou, V. V. Veeravalli. “Population Risk Improvement with Model Compression: An Information-Theoretic Approach,” Entropy 23, no. 10, pp. 1255, Sept. 2021.
  3. Y. Bu, S. Zou, V. V. Veeravalli. “Tightening Mutual Information Based Bounds on Generalization Error,” IEEE Journal on Selected Areas in Information Theory, vol. 1, pp. 121 – 130, May 2020.
  4. C. Wilson, Y. Bu, V. V. Veeravalli. “Adaptive Sequential Machine Learning,” Sequential Analysis, vol. 38, no. 4, Oct. 2019.
  5. Y. Bu, S. Zou, V. V. Veeravalli. “Linear-Complexity Exponentially-Consistent Tests for Universal Outlying Sequence Detection,” IEEE Transactions on Signal Processing, vol. 67, no. 8, pp. 2115-2128, Apr. 2019.
  6. Y. Bu*, S. Zou*, Y. Liang, V. V. Veeravalli. “Estimation of KL Divergence: Optimal Minimax Rate,” (*equal contribution), IEEE Transactions on Information Theory, vol. 64, no. 4, pp. 2648-2674, Apr. 2018.
    Code available at Github

Conference Publications

  1. A. Lancho, A. Weiss, G. Lee, J. Tang, Y. Bu, Y. Polyanskiy, G. W. Wornell. “Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals,” to appear in, IEEE Global Communications Conference, Dec. 2022.
  2. G. Lee, A. Weiss, A. Lancho, J. Tang, Y. Bu, Y. Polyanskiy, G. W. Wornell. “Exploiting Temporal Structures of Cyclostationary Signals for Data-Driven Single-Channel Source Separation,” to appear in, IEEE International Workshop on Machine Learning for Signal Processing, Aug. 2022.
  3. A. Shah*, Y. Bu*, J. K. Lee, P. Sattigeri, R. Panda, S. Das, G. W. Wornell. “Selective Regression under Fairness Criteria,” (* equal contribution), International Conference on Machine Learning (ICML), Jul. 2022. (acceptance rate: 22%)
  4. G. Aminian*, Y. Bu*, G. W. Wornell, M. R. D. Rodrigues. “Tighter Expected Generalization Error Bounds via Convexity of Information Measures,” (* equal contribution), IEEE International Symposium on Information Theory (ISIT), Jun. 2022.
  5. Y. Bu*, J. K. Lee*, P. Sattigeri, R. Panda, G. W. Wornell, L. Karlinsky, R. Feris. “A Maximal Correlation Approach to Imposing Fairness in Machine Learning,” (*equal contribution), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2022.
  6. Y. Bu*, G. Aminian*, L. Toni, M. R. D. Rodrigues, G. W. Wornell. “Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm,” (* equal contribution), International Conference on Artificial Intelligence and Statistics (AISTATS), Mar. 2022. (acceptance rate: 29%)
  7. G. Aminian*, Y. Bu*, L. Toni, M. R. D. Rodrigues, G. W. Wornell. “An Exact Characterization of the Generalization Error for the Gibbs Algorithm,” (* equal contribution), Conference on Neural Information Processing Systems (NeurIPS), Dec. 2021. (acceptance rate: 26%)
  8. Y. Bu*, J. K. Lee*, D. Rajan, P. Sattigeri, R. Panda, S. Das, G. W. Wornell. “Fair Selective Classification via Sufficiency,” (* equal contribution), International Conference on Machine Learning (ICML), Jul. 2021. (Oral, Top 3%)
  9. G. Aminian*, Y. Bu*, L. Toni, M. Rodrigues, G. W. Wornell. “Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information,” (* equal contribution), ICML Workshop on Information-Theoretic Methods for Rigorous, Responsible, and Reliable Machine Learning, Jul. 2021.
  10. Y. Bu, T. Wang, G. W. Wornell. “SDP Methods for Sensitivity-Constrained Privacy Funnel and Information Bottleneck Problems,” IEEE International Symposium on Information Theory (ISIT), Melbourne, Australia, Jul. 2021.
  11. Y. Bu, W. Gao, S. Zou, V. V. Veeravalli. “Information-theoretic Understanding of Population Risk Improvement with Model Compression,” AAAI Conference on Artificial Intelligence (AAAI), New York, Feb. 2020. (acceptance rate: 21%)
  12. Y. Bu, K. Small. “Active Learning in Recommendation Systems with Multi-level User Preferences,” AAAI Workshop on Interactive and Conversational Recommendation Systems (WICRS), New York, Feb. 2020.
  13. Y. Bu, J. Lu, V. V. Veeravalli. “Active and Adaptive Sequential Learning with Per Time-step Excess Risk Guarantees,” IEEE Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Nov. 2019.
  14. Y. Bu, S. Zou, V. V. Veeravalli. “Tightening Mutual Information Based Bounds on Generalization Error,” IEEE International Symposium on Information Theory (ISIT), Paris, France, Jul. 2019.
  15. Y. Bu, J. Lu, V. V. Veeravalli. “Model Change Detection with Application to Machine Learning,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 2019.
  16. Y. Bu, S. Zou, V. V. Veeravalli. “Linear-Complexity Exponentially-Consistent Tests for Universal Outlying Sequence Detection,” IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, Jun. 2017.
  17. Y. Bu, S. Zou, Y. Liang, V. V. Veeravalli. “Estimation of KL Divergence between Large-Alphabet Distributions,” IEEE International Symposium on Information Theory (ISIT), Barcelona, Spain, Jul. 2016.
  18. Y. Bu, S. Zou, Y. Liang, V. V. Veeravalli. “Universal Outlying Sequence Detection for Continuous Observations,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, Mar. 2016