Publications
Selected Publications
- T. Arikan, A. Weiss, H. Vishnu, G. B. Dene, A. C. Singer, and G. W. Wornell, "A Deep Learning Method for Reflective Boundary Estimation", J. Acoust. Soc. Am., vol. 156, no. 1, pp. 65-80, July 2024.
- H. Chen, G. W. Wornell, and Y. Bu, "Gibbs-based Information Criteria and the Over-Parameterized Regime", in Proc. Int. Conf. Artif. Intel., Stat. (AISTATS-2024), (Valencia, Spain), Proc. Mach. Learn. Res. (PMLR), vol. 238, pp. 4501-4509, May 2024.
- Y. Liu, G. W. Wornell, W. T. Freeman, and F. Durand, "Imaging Privacy Threats From an Ambient Light Sensor", Sci. Adv., vol. 10, no. 2, pp. 1-12, January 2024.
- G. Aminian, Y. Bu, L. Toni, M. R. D. Rodrigues, and G. W. Wornell, "Information-Theoretic Characterizations of Generalization Error for the Gibbs Algorithm", IEEE Trans. Inform. Theory, vol. 70, no. 1, pp. 632-655, January 2024.
- T. Jayashankar, G. C. F. Lee, A. Lancho, A. Weiss, Y. Polyanskiy, and G. W. Wornell, "Score-based Source Separation with Applications to Digital Communication Signals", in Advances Neural Inform. Proc. Syst. (NeurIPS-2023), (New Orleans, LA), December 2023.
- M. Jin, A. Yellipeddi, and G. W. Wornell, "2D-Radar Imaging with Deep Convolutional Neural Networks", in Proc. Int. Workshop Mach. Learning, Signal Process. (MLSP-2023), (Rome, Italy), September 2023.
- G. C. F. Lee, "Machine Learning for Data-Driven Signal Separation and Interference Mitigation in Radio-Frequency Communication Systems", Doctoral Thesis, September 2023.
- M. Shen, Y. Bu, and G. W. Wornell, "On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation", in Proc. Int. Conf. Mach. Learning (ICML-2023), (Honolulu, HI), July 2023.
- A. Shah, M. Shen, J. Ryu, S. Das, P. Sattigeri, Y. Bu, and G. W. Wornell, "Group Fairness with Uncertainty in Sensitive Attributes", in ICML 2023 Workshop on Spurious Correlations, Invariance, and Stability (SCIS-203), (Honolulu,HI), July 2023.
- Y. Bu, H. V. Tetali, G. Aminian, M. Rodrigues, and G. W. Wornell, "On the Generalization Error of Meta Learning for the Gibbs Algorithm", in Proc. Int. Symp. Inform. Theory (ISIT-2023), (Taipei, Taiwan), June 2023.