Conference Papers:

  • Z. Lu, D. Guo, A. Bagheri Garakani, K. Liu, A. May, A. Bellet, L. Fan, M. Collins, B. Kingsbury, M. Picheny, F. Sha.
    A Comparison Between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition.
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016.
    [PDF] [Code]
  • A. Bellet, Y. Liang, A. Bagheri Garakani, M.-F. Balcan and F. Sha.
    A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning.
    SIAM International Conference on Data Mining (SDM), 2015.
    [PDF] [ArXiv, Extended PDF] [Slides] [Code]


Technical reports:

  • Z. Lu, A. May, K. Liu, A. Bagheri Garakani, D. Guo, A. Bellet, L. Fan, M. Collins, B. Kingsbury, M. Picheny and F. Sha.
    How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets.
    Technical report, arXiv:1411.4000, 2014.
    [ArXiv, PDF]



  • A. Bagheri Garakani.
    Real-Time Classification of Everyday Fitness Activities on Windows Mobile.
    Senior Thesis. University of Washington Department of Computer Science and Engineering, 2009.
    Best Senior Thesis Award Recipient.
  • A. Bagheri Garakani, V. R. Gadde, E. Tao, J. Diao, Y. Xi, V. Halder, A. Sankar.
    Continuous Language Model Adaptation: Automatically learning domain vocabulary and language statistics.
    Cisco Systems C-Tech Forum (internal conference), 2013.