Statistische Analyse von Nachbarschaftsgraphen

Applicant Professorin Dr. Ulrike von Luxburg

Subject Area Theoretical Computer Science

Term from 2011 to 2015

Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 206679155

Final Report Year 2015

Final Report Abstract

No abstract available

Density estimation from unweighted k-nearest neighbor graphs: a roadmap. In: C. Burges, L. Bottou, Z. Ghahramani, K. Weinberger, (eds), Advances in Neural Information Processing Systems (NIPS). Proceedings of the 26th International Conference on Neural Information Processing Systems, Vol. 1. 2013, pp. 225-233.
U. von Luxburg, M. Alamgir
Density-preserving quantization with Application to graph downsampling. In: M. Balcan and C. Szepesvari (eds), Conference of Learning Theory (COLT). Proceedings of Machine Learning Research, Vol. 35. 2014, pp. 543-559.
M. Alamgir, G. Lugosi, U. von Luxburg
Hitting and commute times in large random neighborhood graphs. Journal of Machine Learning Research, Vol. 15. 2014, Issue 1, pp. 1751-1798.
U. von Luxburg, A. Radl, M. Hein
Local ordinal embedding. In: Proceedings of the 31st International Conference on International Conference on Machine Learning, Vol. 32 . 2014, pp. 847-855.
Y. Terada, U. von Luxburg
Uniqueness of ordinal embedding. In: M. Balcan and C. Szepesvari (eds), Conference on Learning Theory (COLT), Proceedings of Machine Learning Research, Vol. 35.2014, pp. 40-67.
M. Kleindessner, U. von Luxburg
Dimensionality estimation without distances. In: G. Lebanon and S.V.N. Vishwanathan, (eds) Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 38. 2015, pp. 471-479.
M. Kleindessner, U. von Luxburg