
Publications of D Zhou
All genres
Journal Article (2)
1.
Journal Article
21 (15), pp. 3241 - 3247 (2005)
Semi-supervised protein classification using cluster kernels. Bioinformatics 2.
Journal Article
101 (17), pp. 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 Book Chapter (1)
3.
Book Chapter
Discrete Regularization. In: Semi-Supervised Learning, 13, pp. 237 - 250 (Eds.
Conference Paper (9)
4.
Conference Paper
Schölkopf, B.; Platt, J.; Hoffman, T.). Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), Vancouver, BC, Canada, December 04, 2006 - December 07, 2006. MIT Press, Cambridge, MA, USA (2007)
Learning with Hypergraphs: Clustering, Classification, and Embedding. In: Advances in Neural Information Processing Systems 19, pp. 1601 - 1608 (Eds. 5.
Conference Paper
Learning from Labeled and Unlabeled Data on a Directed Graph. In: ICML '05: 22nd international conference on Machine learning, pp. 1036 - 1043 (Eds. Jozef Stefan Institute, Slovenia Program Chairs: Luc D, S.; de Raedt, L.; Wrobel, S.). 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, August 07, 2005 - August 11, 2005. ACM Press, New York, NY, USA (2005)
6.
Conference Paper
Regularization on Discrete Spaces. In: Pattern Recognition: 27th DAGM Symposium, Vienna, Austria, August 31 - September 2, 2005, pp. 361 - 368 (Eds. Kropatsch, W.; Sablatnig, R.; Hanbury, A.). 27th Annual Symposium of the German Association for Pattern Recognition (DAGM 2005), Wien, Austria, August 31, 2005 - September 02, 2005. Springer, Berlin, Germany (2005)
7.
Conference Paper
Semi-supervised Learning on Directed Graphs. In: Advances in Neural Information Processing Systems 17, pp. 1633 - 1640 (Eds. Saul, L.; Weiss, Y.; Bottou, L.). Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), Vancouver, BC, Canada, December 13, 2004 - December 16, 2004. MIT Press, Cambridge, MA, USA (2005)
8.
Conference Paper
Rasmussen, C.; Bülthoff, H.; Schölkopf, B.; Giese, M.). 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Tübingen, Germany, August 30, 2004 - September 01, 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, pp. 237 - 244 (Eds. 9.
Conference Paper
A Regularization Framework for Learning from Graph Data. In: ICML 2004 Workshop on Statistical Relational Learning and Its Connections to Other Fields (SRL 2004), pp. 132 - 137. ICML 2004 Workshop on Statistical Relational Learning and Its Connections to Other Fields (SRL 2004), Banff, Canada, July 08, 2004. (2004)
10.
Conference Paper
Semi-Supervised Protein Classification using Cluster Kernels. Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, December 09, 2003 - December 11, 2003. Advances in Neural Information Processing Systems 16, pp. 595 - 602 (2004)
11.
Conference Paper
Schölkopf, B.). Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, December 08, 2003 - December 13, 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, pp. 321 - 328 (Eds. Thrun, S.; Saul, L.; 12.
Conference Paper
Ranking on Data Manifolds. Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, December 09, 2003 - December 11, 2003. Advances in Neural Information Processing Systems 16, pp. 169 - 176 (2004)
Talk (7)
13.
Talk
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.
Talk
Learning from Labeled and Unlabeled Data on a Directed Graph. The 22nd International Conference on Machine Learning, Bonn, Germany (2005)
15.
Talk
Discrete vs. Continuous: Two Sides of Machine Learning. IBM Watson Research Center, Yorktown Heights, NY, USA (2004)
16.
Talk
How to learn from very few examples? Google Labs, New York, NY, USA (2004)
17.
Talk
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.
Talk
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.
Talk
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)
Report (6)
20.
Report
143). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2005), 13 pp.
Beyond Pairwise Classification and Clustering Using Hypergraphs (Technical Report of the Max Planck Institute for Biological Cybernetics,