| Christoph H. Lampert|
IST Austria (Institute of Science and Technology Austria)
Address: Am Campus 1, IST Austria, 3400 Klosterneuburg, Austria
Email: chl (at) ist (dot) ac (dot) at
Phone: +43 2243 9000 3101 (but sending me email usually works better)
|Latest News||12/2018 Nikola presented his paper "The convergence of sparsified gradient methods" (with D. Alistarh, T. Hoefler, M. Johansson, S. Khirirat, C. Renggli) at NeurIPS 2018 10/2018 A paper accepted to the NeurIPS Workshop "Modeling and decision-making in the spatio-temporal domain". Congratulations Ehsan! 08/2018 A paper accepted to GCPR. Congratulations Remy! 07/2018 A paper accepted to T-PAMI. Congratulations Yongqin! 05/2018 Two papers accepted to ICML. Congratulations Ilja and Georg! 04/2018 Radio Interview (in German) with Christoph Lampert. New: YouTube version 01/2018 IST Austria made it to the Top10 European institutions for Computer Vision and Machine Learning (based on the number of publication at top venues over the last 10 years), according to csrankings.org. It's also #5 for Computer Graphics and #4 for CS Theory. 07/2017 We have released the Animals with Attributes 2 (AwA2) dataset that consists of only free images (e.g. Create Commons licensed). See arXiv 1707.00600 [cs.CV] for details.|
|Recent Publications and Presentations||
Recently on arXiv: Christoph H. Lampert, Liva Ralaivola, Alexander Zimin.
"Dependency-dependent Bounds for Sums of Dependent Random Variables". arXiv:1811.01404 [math.PR]
Recently on arXiv: Alexander Kolesnikov, Christoph H. Lampert, Vittorio Ferrari.
"Detecting Visual Relationships Using Box Attention". arXiv:1807.02136 [cs.CV]
12/2018 NeurIPS 2018 Workshop Modeling and decision-making in the spatiotemporal domain. Ehsan Pajouheshgar, Christoph H. Lampert. "Back to square one: probabilistic trajectory forecasting without bells and whistles". 08/2018 GCPR 2018. Rémy Sun, Christoph H. Lampert. "KS(conf): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications". 07/2018 T-PAMI. Yongqin Xian, Christoph H Lampert, Bernt Schiele, Zeynep Akata. "Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly". 07/2018 ICML 2018. Ilja Kuzborskij, Christoph H. Lampert. "Data-Dependent Stability of Stochastic Gradient Descent". 07/2018 ICML 2018. Subham S. Sahoo, Christoph H. Lampert, Georg Martius. "Learning equations for extrapolation and control". 06/2018 CVPR 2018. Ksenia Konyushkova, Jasper Uijlings, Christoph H. Lampert, Vittorio Ferrari. "Learning Intelligent Dialogs for Bounding Box Annotation".
09/2018 Alex Zimin defended his PhD thesis "Learning from dependent data". Congratulations, Dr Zimin!
02/2018 Alex Kolesnikov defended his PhD thesis "Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images". Congratulations, Dr Kolesnikov!
08/2017 Asya Pentina will join the Swiss Data Science Center in Zurich. All the best!
06/2017 Alex Kolesnikov received a travel award for ICML 2017. Congratulations!
06/2017 Asya Pentina received IST Austria's "Best PhD Thesis Award 2017". Congratulations!
04/2017-09/2017 Christoph Lampert will be on a sabbatical at Google Research in Zurich.
03/2017 Georg Martius moved to Tübingen to head his own research group at the Max-Planck Institute for Intelligent Systems. Congratulations!
11/2016 Asya Pentina defended her PhD Thesis "Theoretical Foundations of Multi-task and Lifelong Learning". Congratulations, Dr Pentina!
|Recent and Upcoming Activities (see CV for a more complete list)|
|Workshops and Edited Volumes||
Workshop: Continuous and Open-Set Learning at CVPR 2017 (with E. Rodner, A. Freytag, T. Boult, J. Denzler)
Edited Volume: Visual Attributes, Springer 2017 (with Rogerio S. Feris and Devi Parikh) Edited Volume: Advanced Structured Prediction, MIT Press 2015 (with S. Nowozin, P. V. Gehler and J. Jancsary)
|Chair Positions and Memberships||
Associate Editor in Chief for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Action Editor for Journal of Machine Learning Research (JMLR)
Editor for International Journal for Computer Vision (IJCV)
Member of the Young Academy of the Austrian Academy of Science
|External Talks||10 Oct 2018:"KS(conf): A Light-Weight Test if a ConvNet Operates Outside of Its Specifications", German Conference on Pattern Recognition (GCPR), Stuttgart 2018.
25 Aug 2018:"Incremental Classifier and Representation Learning", Vision and Sports Summer School Workshop, Prague 2018.
23 May 2018:"Trustworthy Machine Learning", Bosch Center for Artificial Intelligence, Renningen, Germany
30 October 2017:"(Towards) Lifelong Learning", Deepmind, London, UK.
14 September 2017:"(Towards) Lifelong Learning", Computer Vision and Geometry Group (CVG), ETH Zurich, CH.
13 September 2017:"Towards Principled Transfer Learning", Institute for Machine Learning (IML), ETH Zurich, CH.
8 September 2017:"(Towards) Lifelong Learning", Computer Vision Lab (CVL), ETH Zurich, CH.
30 June 2017: "(Towards) Lifelong Machine Learning", MPI for Intelligent Systems, Tübingen, DE.
10 March 2017: "Incremental Classifier and Representation Learning" at IIT-IST workshop on Transfer Learning, Genoa, IT, 2017
9 September 2016: "How to become a Scientist..." and "Computer Vision and Machine Learning at IST Austria" Moscow State University (MSU) and Moscow Institute of Physics and Technology (MIPT), Moscow, RU
28 November 2018: Vienna Graduate School on Computational Optimization, TU Vienna, AT. "Algorithmic Stability and Generalization"- (talk slides PDF
22 August 2018: Vision and Sport Summer School, Prague, CZ. "Machine Learning for Computer Vision"- (talk slides PDF exercise data: ZIP)
18-22 September 2017: Summer Academy of the German National Merit Foundation. Künstliche Intelligenz: Fakten, Chancen, Risiken, Cologne, DE.
21 August 2017: Vision and Sport Summer School, Prague, CZ. "Machine Learning for Computer Vision"- (talk slides PDF exercise data: ZIP)
14 August 2017: Summer School on Graphical Models, Tjärö, Sweden. "Graphical Models for Image Analysis and Synthesis" Slides: ZIP, exercise: ZIP
|Teaching at IST Austria||
Q2 2018/19: "Deep Learning with TensorFlow" (advanced course)
Q1 2018/19: "Statistical Machine Learning" (advanced course)
Q3 2017/18: "Data Science and Scientific Computing" (track core course)
Q2 2017/17: "Deep Learning with TensorFlow" (advanced course)
Q3 2016/17: "Data Science and Scientific Computing" (track core course)
Q2 2016/17: "Probabilistic Graphical Models" (advanced course)
Q1 2016/17: "Computer Vision and Machine Learning" (Introduction to Research at IST Austria)