Tamir Hazan, Ph.D.
Associate professor

Faculty of Industrial Engineering and Management
Technion - Israel Institute of Technology
Bloomfield building, room 503
Technion City, Haifa 32000
tamir.hazan at technion.ac.il

[research]   [papers]  


Research interests

Our research interests involve the theoretical and practical aspects of machine learning. Our research focuses on mathematically founded solutions to modern real life problems that demonstrate non-traditional statistical behavior. Recent examples include efficient learning of high dimensional statistics using Gumbel-max perturbation mdoels in discriminative learning, generative learning and reinforcement learning. We also learn graph based attention models across modalities and consider different aspects of Bayesian deep learning using Gaussian perturbations of their parameters. The practice of our work is motivated by many visual and language problems.

Students

Guy Lorberbom (Ph.D. student)
Itai Gat (Ph.D. student)
Hedda Cohen (Ph.D. student)
Tom Ron (M.Sc. student)
Alon Berliner (M.Sc. student)
Vered Halperin (M.Sc. student)
Igor Drozdov (M.Sc. student)
Hadar Sinai (M.Sc. student)
Assaf Mushkin (M.Sc. student)

Former Students

Alex Schwing. Asisstant professor at UIUC
Alon Cohen. Assistant professor at TAU
Idan Schwartz postdoc at TAU
Adi Manos
Ram Yazdi
Chana Ross
Bar Mayo
Meghan Lahmi
Avrech Ben-David
Gilad Goldreich

Edited Volumes

Perturbations, Optimization, and Statistics (2016)
Tamir Hazan, George Papandreou, Daniel Tarlow (Editors).
Neural Information Processing series, MIT Press.
[MIT Press], [amazon]

Recent papers

  • H. Cohen Indelman, T. Hazan
    Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
    International Conference on Machine Learning (ICML), 2021
  • G. Lorberbom, D. Johnson, C. Maddison, D. Tarlow, T. Hazan
    Learning Generalized Gumbel-max Causal Mechanisms
    Neural Information Processing Systems (NeurIPS), 2021.
  • A. Berliner, G. Rotman, Y. Adi, R. Reichart, T. Hazan
    Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies
    International Conference on Learning Representations (ICLR), 2022.
  • I. Gat, G. Lorberbom, I. Schwartz, T. Hazan
    Latent Space Explanation by Intervention
    Association for the Advancement of Artificial Intelligence (AAAI), 2022
  • A. Ali, I. Schwartz, T. Hazan, L. Wolf
    Video and Text Matching With Conditioned Embeddings
    Winter Conference on Applications of Computer Vision (WACV), 2022
  • A. Manos, T. Hazan, I. Klein
    Walking Direction Estimation Using Smartphone Sensors: A Deep Network-Based Framework
    IEEE Transactions on Instrumentation and Measurement, 2022