| 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)
12/2019 A paper accepted to ICLR. Congratulations Mary!
12/2019 Another paper accepted to WACV. Congratulations Amelie!
12/2019 IST Austria has been approved as ELLIS unit.
09/2019 A paper accepted to WACV. Congratulations Amelie!
09/2019 Asya Pentina (PhD 2016) received an ELLIS Ph.D. award for "outstanding research achievements during the dissertation phase in artificial intelligence and machine learning". Congratulations!
09/2019 A paper accepted to IJCV. Congraluations Remy! 07/2019 A paper accepted as oral to ICCV. Congraluations Mary! 06/2019 Nikola presented his paper Robust learning from untrusted sources at ICML 2019 06/2019 Mary presented her paper Toward understanding knowledge distillation at ICML 2019 05/2019 A paper accepted to the ICML Workshop on Adaptive and Multitask Learning. Congratulations, Alex! 05/2019 A paper accepted to the ICML Workshop on Time Series. Congratulations, Alex! 04/2019 Two papers accepted to ICML. Congratulations Mary and Nikola! 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
|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]
12/2019 NeurIPS 2019 Workshop "ML with Guarantees". Anastasia Pentina, Christoph H. Lampert. "Multi-source domain adaptation with guarantees". 07/2019 ICCV 2019. Mary Phuong, Christoph H. Lampert. "Distillation-Based Training for Multi-Exit Architectures" 06/2019 ICML 2019 Workshop on Adaptive & Multitask Learning. Alexander Zimin, Christoph H. Lampert. "Tasks Without Borders: A New Approach to Online Multi-Task Learning".
06/2019 ICML 2019. Nikola Konstantinov, Christoph H. Lampert. "Robust Learning from Untrusted Sources". 06/2019 ICML 2019. Mary Phuong, Christoph H. Lampert. "Towards Understanding Knowledge Distillation". 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.
|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
25 September 2019: IWRSchool Heidelberg "Transfer Learning" (talk slides PDF)
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||
Q3 2018/19: "Data Science and Scientific Computing" (track core course)
Q2 2018/19: "Deep Learning with TensorFlow" (advanced course)
Q2 2018/19: "Clustering" (guest lecture in IST Austria Core Course 2018/19)
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)