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Greg Shakhnarovich |
Associate Professor Toyota Technological Institute at Chicago 6045 S. Kenwood Ave. Chicago, IL 60637 e-mail gregory at ttic dot edu tel +1 (773) 834-2572 fax +1 (773) 834-9881 |
Research | Teaching | Papers | Personal | Code, data etc. | Vision reading group |
I am an Associate Professor at Toyota Technological Institute ad Chicago (TTIC), a philanthropically endowed
academic computer science institute located on the University of Chicago campus.
I also hold a part-time faculty appointment at the University of Chicago Department of Computer Science.
We at TTIC continue to admit students to our PhD program.
Please contact me for details.
Prior to coming to TTIC, I was a post-doctoral researcher at the Department of Computer Science of Brown University where I worked with
Michael Black.
I received my PhD degree at MIT where I worked at
CSAIL with Trevor
Darrell on computer vision and machine learning. My thesis topic
was Learning Task-Specific Similarity.
Before coming to MIT, I was a graduate student in the Computer Science Department of the Technion, Israel Institute of Technology in Haifa, Israel, where I got my MSc thesis under the advisement of Ran El-Yaniv and Yoram Baram. I got my undergraduate degree in Math and CS from Hebrew University in Jerusalem, Israel.
My CV: PDF
I'm serving as an Area Chair for ICML 2019
H. Jiang, G. Larsson, M. Maire, G. Shakhnarovich, E. Learned-Miller, "Self-Supervised Relative Depth Learning for Urban Scene Understanding", ECCV 2018
M. Mostajabi, M. Maire, G. Shakhnarovich, "Regularizing Deep Networks by Modeling and Predicting Label Structure", CVPR 2018
R. Luo, B. Price, S. Cohen, G. Shakhnarovich, "Discriminability objective for training descriptive captions", CVPR 2018
M. Haris, G. Shakhnarovich, N. Ukita, "Deep backprojection networks for super-resolution", CVPR 2018
Winner of 1st prize in NTIRE 2018 challenge, super-resolution, classic (bicubic) track
PhD thesis, MIT, 2006: Learning Task-Specific Similarity. Advisor: Trevor Darrell.
MsC thesis, Technion, 2001: Statistical Data Cloning for Machine Learning. Advisors: Ran El-Yaniv and Yoram Baram.
N. Kolkin, E. Shechtman, G. Shakhnarovich, "Training Deep Networks to be Spatially Sensitive", ICCV 2017
H. Kamper, S. Settle, G. Shakhnarovich, K. Livescu, "Visually grounded learning of keyword prediction from untranscribed speech", Interspeech 2017 arXiv preprint, 2017
G. Larsson, M. Maire, G. Shakhnarovich, "Colorization as a Proxy Task for Visual Understanding", CVPR 2017 arXiv preprint
R. Luo, G. Shakhnarovich, "Comprehension-guided referring expressions", CVPR 2017 arXiv preprint
M. Mostajabi, N. Kolkin, G. Shakhnarovich, "Diverse Sampling for Self-Supervised Learning of Semantic Segmentation", arXiv preprint, 2016
I. Vasiljevic, A. Chakrabarti, G. Shakhnarovich. "Examining the Impact of Blur on Recognition by Convolutional Networks", arXiv preprint, 2016
T. Kim, J. Keane, W. Wang, H. Tang, J. Riggle, G. Shakhnarovich, D. Brentari, K. Livescu, "Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation", Computer Speech and Language (to appear) arXiv preprint, 2016
G. Larsson, M. Maire, G. Shakhnarovich, "FractalNet: Ultra-Deep Neural Networks without Residuals", ICLR 2017.
most up to date revision, [project page]
A. Chakrabarti, J. Shao, G. Shakhnarovich, "Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions", NIPS 2016 [arXiv preprint], 2016 [project page]
G. Larsson, M. Maire, G. Shakhnarovich, "Learning Representations for Automatic Colorization", ECCV 2016 [pdf]
[arXiv preprint], [project page]
M. Mostajabi, P. Yadollahpour, G. Shakhnarovich, "Feedforward semantic segmentation with zoom-out features", CVPR 2015 [pdf]; current accuracy (mean IoU) on Pascal VOC 2012 test is 69.7, trained only on VOC data.
An earlier (outdated) version: arXiv preprint
S. Trivedi, D. McAllester, G. Shakhnarovich, "Discriminative Metric Learning by Neighborhood Gerrymandering", NIPS 2014 [pdf including supplementary material]
E. Ahmed, G. Shakhnarovich, S. Maji, "Knowing a Good HOG Filter When You See It: Efficient Selection of Filters for Detection", ECCV 2014 (oral) [pdf]
S. Trivedi, J. Wang, S. Kpotufe, G. Shakhnarovich, "A Consistent Estimator of the Expected Gradient Outerproduct", UAI 2014 [pdf]
S. Maji and G. Shakhnarovich, "Part and Attribute Discovery from Relative Annotations", IJCV, vol. 108(1-2), 2014 [pdf]
T. Kim, G. Shakhnarovich, K. Livescu, "Fingerspelling recognition with semi-Markov conditional random fields", ICCV 2013 [pdf]
K. Gimpel, D. Batra, C. Dyer, G. Shakhnarovich, "A Systematic Exploration of Diversity in Machine Translation", EMNLP 2013 [pdf]
P. Kisilev, E. Barkan, G. Shakhnarovich, A. Tzadok, "Learning to detect lesion boundaries in breast ultrasound images", Breast Imaging Workshop, MICCAI 2013 [pdf]
P. Yadollahpour, D. Batra, G. Shakhnarovich, "Discriminative Re-Ranking of Diverse Segmentations", CVPR 2013 [pdf]
Z. Ren, G. Shakhnarovich, "Image Segmentation by Cascaded Region Agglomeration", CVPR 2013 [pdf]
S. Maji, G. Shakhnarovich, "Part Discovery from Partial Correspondence", CVPR 2013 [pdf]
D. Glasner, M. Galun, S. Alpert, R. Basri, G. Shakhnarovich, "Viewpoint-aware object detection and continuous pose estimation", Image and Vision Computing, 30(12), 2012.
D. Batra, P. Yadollahpour, A. Guzman, G. Shakhnarovich, "Diverse M-Best Solutions in Markov Random Fields", ECCV 2012 (oral) [pdf including supplementary material]
T. Kim, K. Livescu, G. Shakhnarovich, "American Sign Language Fingerspelling Recognition with Phonological Feature-Based Tandem Models", IEEE SLT 2012 [pdf]
S. Maji, G. Shakhnarovich, "Part Annotations via Pairwise Correspondence", 4th Workshop on Human Computation, AAAI 2012 [pdf]
D. Glasner, M. Galun, S. Alpert, R. Basri, G. Shakhnarovich, "Viewpoint-Aware Object Detection and Pose Estimation", ICCV 2011. [pdf], project page
G. Shakhnarovich, B. Moghaddam, "Face Recognition in Subspaces", In Handbook of Face Recognition, S. Z. Li and A. K. Jain, Ed. Springer-Verlag, 2nd edition, 2011. [pdf]
T. Kim, G. Shakhnarovich, R. Urtasun, "Sparse Coding for Learning Interpretable Spatio-Temporal Primitives", NIPS, 2010. [pdf], [correction]
C. Vargas-Irwin, G. Shakhnarovich, P. Yadollahpour, J. M. K. Mislow, M. J. Black, J. P. Donoghue, "Decoding Complete Reach and Grasp Actions from Local Primary Motor Cortex Populations", The Journal of Neuroscience, 2010.
A. Ritz, G. Shakhnarovich, A. R. Salomon, B. J. Raphael, "Discovery of Phosphorylation Motif Mixtures in Phosphoproteomics Data". Bioinformatics, 2009. abstract
C. Demiralp, G. Shakhnarovich, S. Zhang, D. H. Laidlaw, "Slicing-based coherence measure for refining clusters of 3D curves." Proceedings of MICCAI Conference, 2008. [pdf]
P. K. Artemiadis, G. Shakhnarovich, C. Vargas-Irwin, J. P. Donoghue, M. J. Black, "Decoding grasp aperture from motor-cortical population activity", IEEE Conf. on Neural Engineering, 2007. [pdf]
G. Shakhnarovich, S.-P. Kim, M. J. Black, "Nonlinear physically-based models for decoding motor-cortical population
activity", NIPS 2006. [pdf]
L. Taycher, G. Shakhnarovich, D. Demirdjian, and T. Darrell,
"Conditional Random People: Tracking Humans with CRFs and Grid
Filters". Proceedings IEEE Conf. on Computer Vision and Pattern
Recognition, 2006. [pdf]
Also in MIT CSAIL Technical Report MIT-CSAIL-2005-079, 2006 [pdf]
N. Srebro, G. Shakhnarovich, S. Roweis, "An Investigation of Computational and Informational Limits in Gaussian Mixture Clustering". ICML, 2006. [pdf] [UoT technical report]
G. Shakhnarovich, J. Fisher, "Performance of Approximate Nearest Neighbor Classification". Poster presented at Machine Learning Workshop at Snowbird, 2006, with preliminary results (work in progress).
G. Shakhnarovich, T. Darrell, P. Indyk, editors, "Nearest-Neighbors methods in Learning and Vision: Theory and Practice". MIT Press, 2006. |
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D. Demirdjian, L. Taycher, G. Shakhnarovich, K. Grauman, T. Darrell, "Avoiding the Streetlight Effect: Tracking by Exploring Likelihood Modes", Proceedings of the International Conference on Computer Vision,2005. [pdf]
L. Ren, G. Shakhnarovich, J. Hodgins, H. Pfister, P. Viola, "Learning Silhouette Features for Control of Human Motion", ACM Transactions on Graphics,2005. [pdf]
O. Aranjelovic, G. Shakhnarovich, J. Fisher, R. Cippola, T. Darrell, "Face Recognition with Image Sets Using Manifold Density Divergence", Proceedings IEEE Conf. on Computer Vision and Pattern Recognition, pp. 581--588, 2005. [pdf]
K. Grauman, G. Shakhnarovich, T. Darrell, "Virtual Visual Hulls: Example-Based 3D Shape Inference from a Single Silhouette", Proceedings of the 2nd Workshop on Statistical Methods in Video Processing,2004. [pdf]
G. Shakhnarovich, P. Viola, T. Darrell, "Fast Pose Estimation with Parameter Sensitive Hashing", Proceedings of the International Conference on Computer Vision,2003.[pdf]
K. Grauman, G. Shakhnarovich, T. Darrell, "Inferring 3D Structure with a Statistical Image-Based Shape Model", Proceedings of the International Conference on Computer Vision,2003. [pdf]
K. Grauman, G. Shakhnarovich, T. Darrell, "A Bayesian Approach to Image-Based Visuall Hull Reconstruction", Proceedings IEEE Conf. on Computer Vision and Pattern Recognition,2003.[pdf]
B. Moghaddam, G. Shakhnarovich, "Boosted Dyadic Kernel Discriminants", NIPS, 2002. [ps]
G. Shakhnarovich, J. W. Fisher, T. Darrell, "Face recognition from long-term observations", Proceedings of European Conference on Computer Vision,2002. [pdf]
G. Shakhnarovich, T. Darrell, "On Probabilistic Combination of Face and Gait Cues for Identification", Proceedings of the Int. Conf. on Automatic Face and Gesture Recognition,2002. [pdf]
G. Shakhnarovich, P. Viola, B. Moghaddam, "A Unified Learning Framework for Real Time Face Detection and Classification", Proceedings of the Int. Conf. on Automatic Face and Gesture Recognition,2002. [pdf]
G. Shakhnarovich, R. El-Yaniv, Y. Baram, "Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation", Proccedings of International Conference on Machine Learning, 2001. [pdf]
G. Shakhnarovich, L. Lee, T. Darrell, "Integrated Face and Gait Recognition From Multiple Views", Proceedings IEEE Conf. on Computer Vision and Pattern Recognition,2001. [pdf]
Kilian Weinberger, Brian Kulis and Dhruv Batra and I organized a NIPS 2011 workshop "Beyond Mahalanobis: Supervised Large-Scale Learning of Similarity".
Workshop presentation: P. Yadollahpour, D. Batra, G. Shakhnarovich, "M-Best Modes: Diverse M-Best Solutions in MRFs", Workshop on Discrete Optimization in Machine Learning, NIPS 2011.
Workshop presentation: D. Batra, G. Shakhnarovich. "Similarity Sensitive Nonlinear Embeddings", Workshop on Kernels and Distances for Computer Vision, ICCV 2011. [pdf]
Winter 2015 | WIS20154421 : Advanced Machine Learning Methods (Weizmann Institute of Science) |
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please fill out this online form ASAP if you are attending the course |
Autumn 2014,2013,2012,2011,2010 | TTIC 31020, Introduction to Statistical Machine Learning |
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Winter 2013,2012,2011 | WIS 20134221, Introduction to Machine Learning (Weizmann Institute of Science) |
Spring 2010 | CS 35040/25040 : Introduction to Computer Vision |
Spring 2009 | TTIC 359 : Large Scale Learning |
Fall 2006 | CS195-5 : CS195-5, Introduction to Machine Learning (Brown) |