Idiap Research Institute
Centre du Parc
Rue Marconi 19
PO Box 592
CH - 1920 Martigny
Switzerland

T +37064560907

 

Ilja Kuzborskij


I am currently a final year PhD student at École polytechnique fédérale de Lausanne (EPFL), advised by Prof. Barbara Caputo and Prof. Francesco Orabona. My current research interest is in design and analysis of efficient transfer learning algorithms.
I am also interested in analysis of non-convex learning problems and nonparametric online learning. See also my CV.

Publications

Machine Learning / Visual Learning

I. Kuzborskij and N. Cesa-Bianchi. Nonparametric Online Regression while Learning the Metric.
     arXiv preprint arXiv:1705.07853, May 2017
      [ PDF ]  [ BIBTEX ] 

@article{kuzborskij2017nonparametric,
  title={{N}onparametric {O}nline {R}egression while {L}earning the {M}etric},
  author={I. Kuzborskij and N. Cesa-Bianchi},
  journal={arXiv preprint arXiv:1705.07853},
  year={2017}
}

I. Kuzborskij and C. H. Lampert. Data-Dependent Stability of Stochastic Gradient Descent.
     arXiv preprint arXiv:1703.01678, March 2017
      [ PDF ]  [ BIBTEX ] 

@article{kuzborskij2017data,
  title={{D}ata-{D}ependent {S}tability of {S}tochastic {G}radient {D}escent},
  author={I. Kuzborskij and C. H. Lampert},
  journal={arXiv preprint arXiv:1703.01678},
  year={2017}
}

I. Kuzborskij and F. Orabona. Fast Rates by Transferring from Auxiliary Hypotheses.
     Machine Learning, September 2016.
      [ PDF ]  [ Link ]  [ BIBTEX ] 

@article{kuzborskij2016fast,
  author={I. Kuzborskij and F. Orabona},
  title={Fast {R}ates by {T}ransferring from {A}uxiliary {H}ypotheses},
  journal="Machine Learning",
  year=2016,
  pages="1--25",
  issn="1573-0565",
  doi="10.1007/s10994-016-5594-4",
  url="http://dx.doi.org/10.1007/s10994-016-5594-4"
}

I. Kuzborskij, F. Orabona, and B. Caputo. Scalable Greedy Algorithms for Transfer Learning.
     Computer Vision and Image Understanding, 2016.
      [ PDF ]  [ Link ]  [ BIBTEX ] 

@article{kuzborskij2016scalable,
  author    = {I. Kuzborskij and
	       F. Orabona and
	       B. Caputo},
  title     = {Transfer {L}earning through {G}reedy {S}ubset {S}election},
  journal = "Computer Vision and Image Understanding ",
  volume = "",
  number = "",
  pages = " - ",
  year = "2016",
  issn = "1077-3142",
  doi = "http://dx.doi.org/10.1016/j.cviu.2016.09.003",
  url = "http://www.sciencedirect.com/science/article/pii/S1077314216301370",
}

I. Kuzborskij, F.M. Carlucci, and B. Caputo. When Naïve Bayes Nearest Neighbors Meet Convolutional Neural Networks.
     IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA. June 2016.
      [ PDF ]  [ BIBTEX ]  [ Supplement ]  [ Code ]

@inproceedings{kuzborskij2016when,
    title={{W}hen {N}aive {B}ayes {N}earest {N}eighbours
	   {M}eet {C}onvolutional {N}eural {N}etworks},
    author={Kuzborskij, I. and Carlucci, F. M. and Caputo, B.},
    booktitle={Computer Vision and Pattern Recognition (CVPR), 2016 IEEE Conference on},
    year={2016}
}

I. Kuzborskij, F. Orabona, and B. Caputo. Transfer Learning through Greedy Subset Selection.   Best Paper Award
     International Conference on Image Analysis and Processing (ICIAP), Genova, Italy. September 2015.
   [ PDF ]  [ BIBTEX ]  [ Code ]

@inproceedings{kuzborskij2015transfer,
  author    = {I. Kuzborskij and
	       F. Orabona and
	       B. Caputo},
  title     = {Transfer Learning Through Greedy Subset Selection},
  booktitle = {Image Analysis and Processing - {ICIAP} 2015 - 18th International
	       Conference, Proceedings, Part
	       {I}},
  pages     = {3--14},
  year      = {2015},
}

I. Kuzborskij and F. Orabona. Stability and Hypothesis Transfer Learning.
     International Conference on Machine Learning (ICML), Atlanta, GA, USA. June 2013.
     [ PDF ]  [ BIBTEX ]  [ Errata ]

@inproceedings{kuzborskij2013stability,
  author    = {I. Kuzborskij and
	       F. Orabona},
  title     = {Stability and {H}ypothesis {T}ransfer {L}earning},
  booktitle = {International Conference on Machine Learning},
  pages     = {942--950},
  year      = {2013}
}

I. Kuzborskij, F. Orabona, and B. Caputo. From N to N+1: Multiclass Transfer Incremental Learning.
     IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, OR, USA. June 2013.
     [ PDF ]  [ BIBTEX ]  [ Code ]  [ Supplement ]

@inproceedings{kuzborskij2013from,
  title =        {From {N} to {N}+1: {M}ulticlass {T}ransfer {I}ncremental {L}earning},
  author =       {Kuzborskij, I. and Orabona, F. and Caputo, B.},
  booktitle={Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on},
  pages={3358--3365},
  year={2013},
  organization={IEEE}
}

Bio-robotics

M. Atzori, A. Gijsberts, I. Kuzborskij, S. Elsig, A.-G. Mittaz Hager, O. Deriaz, C. Castellini, H. Muller, B. Caputo.      Characterization of a Benchmark Database for Myoelectric Movement Classification.
     IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2015/1, Vol. 23.
     [ PDF ]  [ BIBTEX ] 

@article{atzori2015characterization,
  title={Characterization of a {B}enchmark {D}atabase for
	 {M}yoelectric {M}ovement {C}lassification},
  author={Atzori, M. and Gijsberts, A. and Kuzborskij, I. and
	  Elsig, S. and Mittaz Hager, A.-G. and Deriaz, O. and
	  Castellini, C. and Muller, H. and Caputo, B.},
  journal={Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
  volume={23},
  number={1},
  pages={73--83},
  year={2015},
  publisher={IEEE}
}

I. Kuzborskij, A. Gijsberts, B. Caputo.
     On the Challenge of Classifying 52 Hand Movements from Surface Electromyography.
     International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, CA, USA. August 2012.
     [ PDF ]  [ BIBTEX ] 

@inproceedings{kuzborskij2012challenge,
  title={On the {C}hallenge of {C}lassifying 52 {H}and {M}ovements from
	 {S}urface {E}lectromyography},
  author={Kuzborskij, I. and Gijsberts, A. and Caputo, B.},
  booktitle={Engineering in Medicine and Biology Society (EMBC),
	     2012 Annual International Conference of the IEEE},
  pages={4931--4937},
  year={2012},
  organization={IEEE}
}