Publikationen von D Zhou
Alle Typen
Zeitschriftenartikel (2)
1.
Zeitschriftenartikel
21 (15), S. 3241 - 3247 (2005)
Semi-supervised protein classification using cluster kernels. Bioinformatics 2.
Zeitschriftenartikel
101 (17), S. 6559 - 6563 (2004)
Protein ranking: from local to global structure in the protein similarity network. Proceedings of the National Academy of Sciences of the United States of America Buchkapitel (1)
3.
Buchkapitel
Discrete Regularization. In: Semi-Supervised Learning, 13, S. 237 - 250 (Hg.
Konferenzbeitrag (9)
4.
Konferenzbeitrag
Schölkopf, B.; Platt, J.; Hoffman, T.). Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), Vancouver, BC, Canada, 04. Dezember 2006 - 07. Dezember 2006. MIT Press, Cambridge, MA, USA (2007)
Learning with Hypergraphs: Clustering, Classification, and Embedding. In: Advances in Neural Information Processing Systems 19, S. 1601 - 1608 (Hg. 5.
Konferenzbeitrag
Learning from Labeled and Unlabeled Data on a Directed Graph. In: ICML '05: 22nd international conference on Machine learning, S. 1036 - 1043 (Hg. Jozef Stefan Institute, Slovenia Program Chairs: Luc D, S.; de Raedt, L.; Wrobel, S.). 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, 07. August 2005 - 11. August 2005. ACM Press, New York, NY, USA (2005)
6.
Konferenzbeitrag
Regularization on Discrete Spaces. In: Pattern Recognition: 27th DAGM Symposium, Vienna, Austria, August 31 - September 2, 2005, S. 361 - 368 (Hg. Kropatsch, W.; Sablatnig, R.; Hanbury, A.). 27th Annual Symposium of the German Association for Pattern Recognition (DAGM 2005), Wien, Austria, 31. August 2005 - 02. September 2005. Springer, Berlin, Germany (2005)
7.
Konferenzbeitrag
Semi-supervised Learning on Directed Graphs. In: Advances in Neural Information Processing Systems 17, S. 1633 - 1640 (Hg. Saul, L.; Weiss, Y.; Bottou, L.). Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), Vancouver, BC, Canada, 13. Dezember 2004 - 16. Dezember 2004. MIT Press, Cambridge, MA, USA (2005)
8.
Konferenzbeitrag
Rasmussen, C.; Bülthoff, H.; Schölkopf, B.; Giese, M.). 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Tübingen, Germany, 30. August 2004 - 01. September 2004. Springer, Berlin, Germany (2004)
Learning from Labeled and Unlabeled Data Using Random Walks. In: Pattern Recognition: 26th DAGM Symposium, Tübingen, Germany, August 30 - September 1, 2004, S. 237 - 244 (Hg. 9.
Konferenzbeitrag
A Regularization Framework for Learning from Graph Data. In: ICML 2004 Workshop on Statistical Relational Learning and Its Connections to Other Fields (SRL 2004), S. 132 - 137. ICML 2004 Workshop on Statistical Relational Learning and Its Connections to Other Fields (SRL 2004), Banff, Canada, 08. Juli 2004. (2004)
10.
Konferenzbeitrag
Semi-Supervised Protein Classification using Cluster Kernels. Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, 09. Dezember 2003 - 11. Dezember 2003. Advances in Neural Information Processing Systems 16, S. 595 - 602 (2004)
11.
Konferenzbeitrag
Schölkopf, B.). Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, 08. Dezember 2003 - 13. Dezember 2003. MIT Press, Cambridge, MA, USA (2004)
Learning with Local and Global Consistency. In: Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference, S. 321 - 328 (Hg. Thrun, S.; Saul, L.; 12.
Konferenzbeitrag
Ranking on Data Manifolds. Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, 09. Dezember 2003 - 11. Dezember 2003. Advances in Neural Information Processing Systems 16, S. 169 - 176 (2004)
Vortrag (7)
13.
Vortrag
Beyond pairwise classification and clustering using hypergraphs. NIPS Workshop on Computational Biology and the Analysis of Heterogeneous Data (MLCB 2005), Whistler, BC, Canada (2005)
14.
Vortrag
Learning from Labeled and Unlabeled Data on a Directed Graph. The 22nd International Conference on Machine Learning, Bonn, Germany (2005)
15.
Vortrag
Discrete vs. Continuous: Two Sides of Machine Learning. IBM Watson Research Center, Yorktown Heights, NY, USA (2004)
16.
Vortrag
How to learn from very few examples? Google Labs, New York, NY, USA (2004)
17.
Vortrag
Discrete vs. Continuous: Two Sides of Machine Learning. Department of Computer Science, and the Center of Computational Learning Systems: Columbia University, New York, NY, USA (2004)
18.
Vortrag
Riemannian Geometry on Graphs and its Application to Ranking and Classification. DIMACS Working Group on The Mathematics of Web Search and Meta-Search, Bertorino, Italy (2004)
19.
Vortrag
Learning from Labeled and Unlabeled Data: Semi-supervised Learning and Ranking. The Natural Language Computing Group of Microsoft Research Asia, and the Institute of System Sciences, the Chinese Academy of Sciences, Beijing, China (2004)
Bericht (6)
20.
Bericht
143). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2005), 13 S.
Beyond Pairwise Classification and Clustering Using Hypergraphs (Technical Report of the Max Planck Institute for Biological Cybernetics,