Signals, Information, and Algorithms Laboratory
Professor Gregory W. Wornell


Selected Publications

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. G. C. F. Lee, "Machine Learning for Data-Driven Signal Separation and Interference Mitigation in Radio-Frequency Communication Systems", Doctoral Thesis, September 2023.
  8. 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.
  9. 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.
  10. 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.