Items where Author is "Lapin, Maksim"

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: Item Type | No Grouping
Jump to: Conference or Workshop Item (A Paper) | Article
Number of items: 6.

Conference or Workshop Item (A Paper)

Lapin, Maksim and Hein, Matthias and Schiele, Bernt
(2016) Loss Functions for Top-k Error: Analysis and Insights.
In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR'16).
Conference: CVPR IEEE Conference on Computer Vision and Pattern Recognition

Jawanpuria, Pratik and Lapin, Maksim and Hein, Matthias and Schiele, Bernt
(2015) Efficient Output Kernel Learning for Multiple Tasks.
In: Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada.
Conference: NeurIPS Conference on Neural Information Processing Systems

Lapin, Maksim and Hein, Matthias and Schiele, Bernt
(2015) Top-k Multiclass SVM.
In: Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada.
Conference: NeurIPS Conference on Neural Information Processing Systems

Lapin, Maksim and Schiele, Bernt and Hein, Matthias
(2014) Scalable Multitask Representation Learning for Scene Classification.
In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, OH, USA, June 23-28, 2014.
Conference: CVPR IEEE Conference on Computer Vision and Pattern Recognition

Lapin, Maksim and Mikeev, Linar and Wolf, Verena
(2011) SHAVE: stochastic hybrid analysis of markov population models.
In: Proceedings of the 14th ACM International Conference on Hybrid Systems: Computation and Control, HSCC 2011, Chicago, IL, USA, April 12-14, 2011.

Article

Lapin, Maksim and Hein, Matthias and Schiele, Bernt
(2014) Learning using privileged information: SV M+ and weighted SVM.
Neural Networks, 53. pp. 95-108.

This list was generated on Thu Nov 21 11:53:51 2024 CET.
CISPA is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.