Edward Raff



  1. F. Lu, E. Raff, and F. Ferraro, "Neural Bregman Divergences for Distance Learning", InProceedings, 11th International Conference on Learning Representations, May 2023, 28 downloads.


  1. F. Lu, J. Munoz, M. Fuchs, T. LeBlond, E. Zaresky-Williams, E. Raff, F. Ferraro, and B. Testa, "A General Framework for Auditing Differentially Private Machine Learning", InProceedings, Advances in Neural Information Processing Systems, November 2022, 41 downloads.
  2. G. Y. Kebe, L. E. Richards, E. Raff, F. Ferraro, and C. Matuszek, "Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech", InProceedings, Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), June 2022, 27 downloads.
  3. F. Lu, F. Ferraro, and E. Raff, "Continuously Generalized Ordinal Regression for Linear and Deep Models", InProceedings, SIAM International Conference on Data Mining, April 2022, 128 downloads.


  1. N. Pillai, E. Raff, F. Ferraro, and C. Matuszek, "Sampling Approach Matters: Active Learning for Robotic Language Acquisition", InProceedings, IEEE BigData BDML, December 2020, 533 downloads.
  2. A. T. Nguyen, L. E. Richards, G. Y. Kebe, E. Raff, K. Darvish, F. Ferraro, and C. Matuszek, "Practical Cross-modal Manifold Alignment for Grounded Language", Article, arXiv:2009.05147 [cs.CV], September 2020, 204 downloads.
  3. P. Jenkins, R. Sachdeva, G. Y. Kebe, P. Higgins, K. Darvish, E. Raff, D. Engel, J. Winder, F. Ferraro, and C. Matuszek, "Presentation and Analysis of a Multimodal Dataset for Grounded Language Learning", Article, arXiv:2007.14987 [cs.RO], July 2020, 211 downloads.