24. ICML 2007:
Corvalis,
Oregon,
USA
Zoubin Ghahramani (Ed.):
Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvalis, Oregon, USA, June 20-24, 2007.
ACM International Conference Proceeding Series 227 ACM 2007, ISBN 978-1-59593-793-3 BibTeX
- Esma Aïmeur, Gilles Brassard, Sébastien Gambs:
Quantum clustering algorithms.
1-8
Electronic Edition (ACM DL) BibTeX
- Alekh Agarwal, Soumen Chakrabarti:
Learning random walks to rank nodes in graphs.
9-16
Electronic Edition (ACM DL) BibTeX
- Yonatan Amit, Michael Fink, Nathan Srebro, Shimon Ullman:
Uncovering shared structures in multiclass classification.
17-24
Electronic Edition (ACM DL) BibTeX
- Rie Kubota Ando, Tong Zhang:
Two-view feature generation model for semi-supervised learning.
25-32
Electronic Edition (ACM DL) BibTeX
- Galen Andrew, Jianfeng Gao:
Scalable training of L1-regularized log-linear models.
33-40
Electronic Edition (ACM DL) BibTeX
- S. Asharaf, M. Narasimha Murty, Shirish Krishnaj Shevade:
Multiclass core vector machine.
41-48
Electronic Edition (ACM DL) BibTeX
- Arik Azran:
The rendezvous algorithm: multiclass semi-supervised learning with Markov random walks.
49-56
Electronic Edition (ACM DL) BibTeX
- Rashmin Babaria, J. Saketha Nath, S. Krishnan, K. R. Sivaramakrishnan, Chiranjib Bhattacharyya, M. Narasimha Murty:
Focused crawling with scalable ordinal regression solvers.
57-64
Electronic Edition (ACM DL) BibTeX
- Aharon Bar-Hillel, Daphna Weinshall:
Learning distance function by coding similarity.
65-72
Electronic Edition (ACM DL) BibTeX
- Sourangshu Bhattacharya, Chiranjib Bhattacharyya, Nagasuma Chandra:
Structural alignment based kernels for protein structure classification.
73-80
Electronic Edition (ACM DL) BibTeX
- Steffen Bickel, Michael Brückner, Tobias Scheffer:
Discriminative learning for differing training and test distributions.
81-88
Electronic Edition (ACM DL) BibTeX
- Antoine Bordes, Léon Bottou, Patrick Gallinari, Jason Weston:
Solving multiclass support vector machines with LaRank.
89-96
Electronic Edition (ACM DL) BibTeX
- Brent Bryan, H. Brendan McMahan, Chad M. Schafer, Jeff G. Schneider:
Efficiently computing minimax expected-size confidence regions.
97-104
Electronic Edition (ACM DL) BibTeX
- Razvan C. Bunescu, Raymond J. Mooney:
Multiple instance learning for sparse positive bags.
105-112
Electronic Edition (ACM DL) BibTeX
- Ludwig M. Busse, Peter Orbanz, Joachim M. Buhmann:
Cluster analysis of heterogeneous rank data.
113-120
Electronic Edition (ACM DL) BibTeX
- Bin Cao, Dou Shen, Jian-Tao Sun, Qiang Yang, Zheng Chen:
Feature selection in a kernel space.
121-128
Electronic Edition (ACM DL) BibTeX
- Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Hang Li:
Learning to rank: from pairwise approach to listwise approach.
129-136
Electronic Edition (ACM DL) BibTeX
- Luca Cazzanti, Maya R. Gupta:
Local similarity discriminant analysis.
137-144
Electronic Edition (ACM DL) BibTeX
- Antoni B. Chan, Nuno Vasconcelos, Gert R. G. Lanckriet:
Direct convex relaxations of sparse SVM.
145-153
Electronic Edition (ACM DL) BibTeX
- Xue-wen Chen, Jong Cheol Jeong:
Minimum reference set based feature selection for small sample classifications.
153-160
Electronic Edition (ACM DL) BibTeX
- Li Cheng, S. V. N. Vishwanathan:
Learning to compress images and videos.
161-168
Electronic Edition (ACM DL) BibTeX
- Corinna Cortes, Mehryar Mohri, Ashish Rastogi:
Magnitude-preserving ranking algorithms.
169-176
Electronic Edition (ACM DL) BibTeX
- Alexandre d'Aspremont, Francis R. Bach, Laurent El Ghaoui:
Full regularization path for sparse principal component analysis.
177-184
Electronic Edition (ACM DL) BibTeX
- Guang Dai, Dit-Yan Yeung:
Kernel selection forl semi-supervised kernel machines.
185-192
Electronic Edition (ACM DL) BibTeX
- Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu:
Boosting for transfer learning.
193-200
Electronic Edition (ACM DL) BibTeX
- Ian Davidson, S. S. Ravi:
Intractability and clustering with constraints.
201-208
Electronic Edition (ACM DL) BibTeX
- Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon:
Information-theoretic metric learning.
209-216
Electronic Edition (ACM DL) BibTeX
- Jesse Davis, Vítor Santos Costa, Soumya Ray, David Page:
An integrated approach to feature invention and model construction for drug activity prediction.
217-224
Electronic Edition (ACM DL) BibTeX
- Erick Delage, Shie Mannor:
Percentile optimization in uncertain Markov decision processes with application to efficient exploration.
225-232
Electronic Edition (ACM DL) BibTeX
- Laura Dietz, Steffen Bickel, Tobias Scheffer:
Unsupervised prediction of citation influences.
233-240
Electronic Edition (ACM DL) BibTeX
- Piotr Dollár, Vincent Rabaud, Serge J. Belongie:
Non-isometric manifold learning: analysis and an algorithm.
241-248
Electronic Edition (ACM DL) BibTeX
- Miroslav Dudík, David M. Blei, Robert E. Schapire:
Hierarchical maximum entropy density estimation.
249-256
Electronic Edition (ACM DL) BibTeX
- Roberto Esposito, Daniele P. Radicioni:
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers.
257-264
Electronic Edition (ACM DL) BibTeX
- Amir Massoud Farahmand, Csaba Szepesvári, Jean-Yves Audibert:
Manifold-adaptive dimension estimation.
265-272
Electronic Edition (ACM DL) BibTeX
- Sylvain Gelly, David Silver:
Combining online and offline knowledge in UCT.
273-280
Electronic Edition (ACM DL) BibTeX
- Samuel Gerber, Tolga Tasdizen, Ross T. Whitaker:
Robust non-linear dimensionality reduction using successive 1-dimensional Laplacian Eigenmaps.
281-288
Electronic Edition (ACM DL) BibTeX
- Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc:
Gradient boosting for kernelized output spaces.
289-296
Electronic Edition (ACM DL) BibTeX
- Mohammad Ghavamzadeh, Yaakov Engel:
Bayesian actor-critic algorithms.
297-304
Electronic Edition (ACM DL) BibTeX
- Amir Globerson, Terry Koo, Xavier Carreras, Michael Collins:
Exponentiated gradient algorithms for log-linear structured prediction.
305-312
Electronic Edition (ACM DL) BibTeX
- Nizar Grira, Michael E. Houle:
Best of both: a hybridized centroid-medoid clustering heuristic.
313-320
Electronic Edition (ACM DL) BibTeX
- Fan Guo, Steve Hanneke, Wenjie Fu, Eric P. Xing:
Recovering temporally rewiring networks: a model-based approach.
321-328
Electronic Edition (ACM DL) BibTeX
- Rahul Gupta, Ajit A. Diwan, Sunita Sarawagi:
Efficient inference with cardinality-based clique potentials.
329-336
Electronic Edition (ACM DL) BibTeX
- Romain Hérault, Yves Grandvalet:
Sparse probabilistic classifiers.
337-344
Electronic Edition (ACM DL) BibTeX
- Peter Haider, Ulf Brefeld, Tobias Scheffer:
Supervised clustering of streaming data for email batch detection.
345-352
Electronic Edition (ACM DL) BibTeX
- Steve Hanneke:
A bound on the label complexity of agnostic active learning.
353-360
Electronic Edition (ACM DL) BibTeX
- Steven C. H. Hoi, Rong Jin, Michael R. Lyu:
Learning nonparametric kernel matrices from pairwise constraints.
361-368
Electronic Edition (ACM DL) BibTeX
- Manfred Jaeger:
Parameter learning for relational Bayesian networks.
369-376
Electronic Edition (ACM DL) BibTeX
- Shihao Ji, Lawrence Carin:
Bayesian compressive sensing and projection optimization.
377-384
Electronic Edition (ACM DL) BibTeX
- Jeffrey Johns, Sridhar Mahadevan:
Constructing basis functions from directed graphs for value function approximation.
385-392
Electronic Edition (ACM DL) BibTeX
- Kristian Kersting, Christian Plagemann, Patrick Pfaff, Wolfram Burgard:
Most likely heteroscedastic Gaussian process regression.
393-400
Electronic Edition (ACM DL) BibTeX
- Kye-Hyeon Kim, Seungjin Choi:
Neighbor search with global geometry: a minimax message passing algorithm.
401-408
Electronic Edition (ACM DL) BibTeX
- Minyoung Kim, Vladimir Pavlovic:
A recursive method for discriminative mixture learning.
409-416
Electronic Edition (ACM DL) BibTeX
- Sergey Kirshner, Padhraic Smyth:
Infinite mixtures of trees.
417-423
Electronic Edition (ACM DL) BibTeX
- Arto Klami, Samuel Kaski:
Local dependent components.
425-432
Electronic Edition (ACM DL) BibTeX
- Stanley Kok, Pedro Domingos:
Statistical predicate invention.
433-440
Electronic Edition (ACM DL) BibTeX
- Nicole Krämer, Mikio L. Braun:
Kernelizing PLS, degrees of freedom, and efficient model selection.
441-448
Electronic Edition (ACM DL) BibTeX
- Andreas Krause, Carlos Guestrin:
Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach.
449-456
Electronic Edition (ACM DL) BibTeX
- Dmitry Kropotov, Dmitry Vetrov:
On one method of non-diagonal regularization in sparse Bayesian learning.
457-464
Electronic Edition (ACM DL) BibTeX
- Dima Kuzmin, Manfred K. Warmuth:
Online kernel PCA with entropic matrix updates.
465-472
Electronic Edition (ACM DL) BibTeX
- Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio:
An empirical evaluation of deep architectures on problems with many factors of variation.
473-480
Electronic Edition (ACM DL) BibTeX
- Neil D. Lawrence, Andrew J. Moore:
Hierarchical Gaussian process latent variable models.
481-488
Electronic Edition (ACM DL) BibTeX
- Su-In Lee, Vassil Chatalbashev, David Vickrey, Daphne Koller:
Learning a meta-level prior for feature relevance from multiple related tasks.
489-496
Electronic Edition (ACM DL) BibTeX
- Jure Leskovec, Christos Faloutsos:
Scalable modeling of real graphs using Kronecker multiplication.
497-504
Electronic Edition (ACM DL) BibTeX
- Bin Li, Mingmin Chi, Jianping Fan, Xiangyang Xue:
Support cluster machine.
505-512
Electronic Edition (ACM DL) BibTeX
- Fuxin Li, Jian Yang, Jue Wang:
A transductive framework of distance metric learning by spectral dimensionality reduction.
513-520
Electronic Edition (ACM DL) BibTeX
- Chris H. Q. Ding, Tao Li:
Adaptive dimension reduction using discriminant analysis and K-means clustering.
521-528
Electronic Edition (ACM DL) BibTeX
- Wenye Li, Kin-Hong Lee, Kwong-Sak Leung:
Large-scale RLSC learning without agony.
529-536
Electronic Edition (ACM DL) BibTeX
- Xin Li, William Kwok-Wai Cheung, Jiming Liu, Zhili Wu:
A novel orthogonal NMF-based belief compression for POMDPs.
537-544
Electronic Edition (ACM DL) BibTeX
- Percy Liang, Michael I. Jordan, Benjamin Taskar:
A permutation-augmented sampler for DP mixture models.
545-552
Electronic Edition (ACM DL) BibTeX
- Xuejun Liao, Hui Li, Lawrence Carin:
Quadratically gated mixture of experts for incomplete data classification.
553-560
Electronic Edition (ACM DL) BibTeX
- Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi:
Trust region Newton methods for large-scale logistic regression.
561-568
Electronic Edition (ACM DL) BibTeX
- Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip S. Yu:
Relational clustering by symmetric convex coding.
569-576
Electronic Edition (ACM DL) BibTeX
- Yong Ma, Shihong Lao, Erina Takikawa, Masato Kawade:
Discriminant analysis in correlation similarity measure space.
577-584
Electronic Edition (ACM DL) BibTeX
- Sridhar Mahadevan:
Adaptive mesh compression in 3D computer graphics using multiscale manifold learning.
585-592
Electronic Edition (ACM DL) BibTeX
- Gideon S. Mann, Andrew McCallum:
Simple, robust, scalable semi-supervised learning via expectation regularization.
593-600
Electronic Edition (ACM DL) BibTeX
- Bhaskara Marthi:
Automatic shaping and decomposition of reward functions.
601-608
Electronic Edition (ACM DL) BibTeX
- Hamed Masnadi-Shirazi, Nuno Vasconcelos:
Asymmetric boosting.
609-619
Electronic Edition (ACM DL) BibTeX
- Graham McNeill, Sethu Vijayakumar:
Linear and nonlinear generative probabilistic class models for shape contours.
617-624
Electronic Edition (ACM DL) BibTeX
- Lilyana Mihalkova, Raymond J. Mooney:
Bottom-up learning of Markov logic network structure.
625-632
Electronic Edition (ACM DL) BibTeX
- David M. Mimno, Wei Li, Andrew McCallum:
Mixtures of hierarchical topics with Pachinko allocation.
633-640
Electronic Edition (ACM DL) BibTeX
- Andriy Mnih, Geoffrey E. Hinton:
Three new graphical models for statistical language modelling.
641-648
Electronic Edition (ACM DL) BibTeX
- Alessandro Moschitti, Fabio Massimo Zanzotto:
Fast and effective kernels for relational learning from texts.
649-656
Electronic Edition (ACM DL) BibTeX
- Sofia Mosci, Lorenzo Rosasco, Alessandro Verri:
Dimensionality reduction and generalization.
657-664
Electronic Edition (ACM DL) BibTeX
- Markos Mylonakis, Khalil Sima'an, Rebecca Hwa:
Unsupervised estimation for noisy-channel models.
665-672
Electronic Edition (ACM DL) BibTeX
- Blaine Nelson, Ira Cohen:
Revisiting probabilistic models for clustering with pair-wise constraints.
673-680
Electronic Edition (ACM DL) BibTeX
- Nam Nguyen, Yunsong Guo:
Comparisons of sequence labeling algorithms and extensions.
681-688
Electronic Edition (ACM DL) BibTeX
- Kai Ni, Lawrence Carin, David B. Dunson:
Multi-task learning for sequential data via iHMMs and the nested Dirichlet process.
689-696
Electronic Edition (ACM DL) BibTeX
- Jens Nilsson, Fei Sha, Michael I. Jordan:
Regression on manifolds using kernel dimension reduction.
697-704
Electronic Edition (ACM DL) BibTeX
- Sarah Osentoski, Sridhar Mahadevan:
Learning state-action basis functions for hierarchical MDPs.
705-712
Electronic Edition (ACM DL) BibTeX
- A. P. Yogananda, M. Narasimha Murty, Lakshmi Gopal:
A fast linear separability test by projection of positive points on subspaces.
713-720
Electronic Edition (ACM DL) BibTeX
- Sandeep Pandey, Deepayan Chakrabarti, Deepak Agarwal:
Multi-armed bandit problems with dependent arms.
721-728
Electronic Edition (ACM DL) BibTeX
- Charles Parker, Alan Fern, Prasad Tadepalli:
Learning for efficient retrieval of structured data with noisy queries.
729-736
Electronic Edition (ACM DL) BibTeX
- Ronald Parr, Christopher Painter-Wakefield, Lihong Li, Michael L. Littman:
Analyzing feature generation for value-function approximation.
737-744
Electronic Edition (ACM DL) BibTeX
- Jan Peters, Stefan Schaal:
Reinforcement learning by reward-weighted regression for operational space control.
745-750
Electronic Edition (ACM DL) BibTeX
- Chee Wee Phua, Robert Fitch:
Tracking value function dynamics to improve reinforcement learning with piecewise linear function approximation.
751-758
Electronic Edition (ACM DL) BibTeX
- Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer, Andrew Y. Ng:
Self-taught learning: transfer learning from unlabeled data.
759-766
Electronic Edition (ACM DL) BibTeX
- Alexander Rakhlin, Jacob Abernethy, Peter L. Bartlett:
Online discovery of similarity mappings.
767-774
Electronic Edition (ACM DL) BibTeX
- Alain Rakotomamonjy, Francis Bach, Stéphane Canu, Yves Grandvalet:
More efficiency in multiple kernel learning.
775-782
Electronic Edition (ACM DL) BibTeX
- Matthew J. Rattigan, Marc Maier, David Jensen:
Graph clustering with network structure indices.
783-790
Electronic Edition (ACM DL) BibTeX
- Ruslan Salakhutdinov, Andriy Mnih, Geoffrey E. Hinton:
Restricted Boltzmann machines for collaborative filtering.
791-798
Electronic Edition (ACM DL) BibTeX
- Mohak Shah:
Sample compression bounds for decision trees.
799-806
Electronic Edition (ACM DL) BibTeX
- Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro:
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM.
807-814
Electronic Edition (ACM DL) BibTeX
- Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt:
A dependence maximization view of clustering.
815-822
Electronic Edition (ACM DL) BibTeX
- Le Song, Alex J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo:
Supervised feature selection via dependence estimation.
823-830
Electronic Edition (ACM DL) BibTeX
- Bharath K. Sriperumbudur, David A. Torres, Gert R. G. Lanckriet:
Sparse eigen methods by D.C. programming.
831-838
Electronic Edition (ACM DL) BibTeX
- David H. Stern, Ralf Herbrich, Thore Graepel:
Learning to solve game trees.
839-846
Electronic Edition (ACM DL) BibTeX
- Jianyong Sun, Ata Kabán, Somak Raychaudhury:
Robust mixtures in the presence of measurement errors.
847-854
Electronic Edition (ACM DL) BibTeX
- Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf, Kenji Fukumizu:
A kernel-based causal learning algorithm.
855-862
Electronic Edition (ACM DL) BibTeX
- Charles A. Sutton, Andrew McCallum:
Piecewise pseudolikelihood for efficient training of conditional random fields.
863-870
Electronic Edition (ACM DL) BibTeX
- Richard S. Sutton, Anna Koop, David Silver:
On the role of tracking in stationary environments.
871-878
Electronic Edition (ACM DL) BibTeX
- Matthew E. Taylor, Peter Stone:
Cross-domain transfer for reinforcement learning.
879-886
Electronic Edition (ACM DL) BibTeX
- Ivan Titov, James Henderson:
Incremental Bayesian networks for structure prediction.
887-894
Electronic Edition (ACM DL) BibTeX
- Ryota Tomioka, Kazuyuki Aihara:
Classifying matrices with a spectral regularization.
895-902
Electronic Edition (ACM DL) BibTeX
- Petroula Tsampouka, John Shawe-Taylor:
Approximate maximum margin algorithms with rules controlled by the number of mistakes.
903-910
Electronic Edition (ACM DL) BibTeX
- Ivor W. Tsang, András Kocsor, James T. Kwok:
Simpler core vector machines with enclosing balls.
911-918
Electronic Edition (ACM DL) BibTeX
- Koji Tsuda:
Entire regularization paths for graph data.
919-926
Electronic Edition (ACM DL) BibTeX
- Raquel Urtasun, Trevor Darrell:
Discriminative Gaussian process latent variable model for classification.
927-934
Electronic Edition (ACM DL) BibTeX
- Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano:
Experimental perspectives on learning from imbalanced data.
935-942
Electronic Edition (ACM DL) BibTeX
- Gabriel Wachman, Roni Khardon:
Learning from interpretations: a rooted kernel for ordered hypergraphs.
943-950
Electronic Edition (ACM DL) BibTeX
- Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky:
A kernel path algorithm for support vector machines.
951-958
Electronic Edition (ACM DL) BibTeX
- Hua-Yan Wang, Hongbin Zha, Hong Qin:
Dirichlet aggregation: unsupervised learning towards an optimal metric for proportional data.
959-966
Electronic Edition (ACM DL) BibTeX
- Huan Wang, Shuicheng Yan, Thomas S. Huang, Jianzhuang Liu, Xiaoou Tang:
Transductive regression piloted by inter-manifold relations.
967-974
Electronic Edition (ACM DL) BibTeX
- Jack M. Wang, David J. Fleet, Aaron Hertzmann:
Multifactor Gaussian process models for style-content separation.
975-982
Electronic Edition (ACM DL) BibTeX
- Li Wang, Ji Zhu, Hui Zou:
Hybrid huberized support vector machines for microarray classification.
983-990
Electronic Edition (ACM DL) BibTeX
- Liwei Wang, Cheng Yang, Jufu Feng:
On learning with dissimilarity functions.
991-998
Electronic Edition (ACM DL) BibTeX
- Manfred K. Warmuth:
Winnowing subspaces.
999-1006
Electronic Edition (ACM DL) BibTeX
- Tomás Werner:
What is decreased by the max-sum arc consistency algorithm?
1007-1014
Electronic Edition (ACM DL) BibTeX
- Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepalli:
Multi-task reinforcement learning: a hierarchical Bayesian approach.
1015-1022
Electronic Edition (ACM DL) BibTeX
- David P. Wipf, Srikantan Nagarajan:
Beamforming using the relevance vector machine.
1023-1030
Electronic Edition (ACM DL) BibTeX
- Adam Woznica, Alexandros Kalousis, Melanie Hilario:
Learning to combine distances for complex representations.
1031-1038
Electronic Edition (ACM DL) BibTeX
- Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schölkopf:
Local learning projections.
1039-1046
Electronic Edition (ACM DL) BibTeX
- Yuehua Xu, Alan Fern:
On learning linear ranking functions for beam search.
1047-1054
Electronic Edition (ACM DL) BibTeX
- Xiang Xuan, Kevin P. Murphy:
Modeling changing dependency structure in multivariate time series.
1055-1062
Electronic Edition (ACM DL) BibTeX
- Ya Xue, David B. Dunson, Lawrence Carin:
The matrix stick-breaking process for flexible multi-task learning.
1063-1070
Electronic Edition (ACM DL) BibTeX
- Takehisa Yairi:
Map building without localization by dimensionality reduction techniques.
1071-1078
Electronic Edition (ACM DL) BibTeX
- Keisuke Yamazaki, Motoaki Kawanabe, Sumio Watanabe, Masashi Sugiyama, Klaus-Robert Müller:
Asymptotic Bayesian generalization error when training and test distributions are different.
1079-1086
Electronic Edition (ACM DL) BibTeX
- Jieping Ye:
Least squares linear discriminant analysis.
1087-1093
Electronic Edition (ACM DL) BibTeX
- Jieping Ye, Jianhui Chen, Shuiwang Ji:
Discriminant kernel and regularization parameter learning via semidefinite programming.
1095-1102
Electronic Edition (ACM DL) BibTeX
- Shipeng Yu, Volker Tresp, Kai Yu:
Robust multi-task learning with t-processes.
1103-1110
Electronic Edition (ACM DL) BibTeX
- Jian Zhang, Rong Yan:
On the value of pairwise constraints in classification and consistency.
1111-1118
Electronic Edition (ACM DL) BibTeX
- Kai Zhang, Ivor W. Tsang, James T. Kwok:
Maximum margin clustering made practical.
1119-1126
Electronic Edition (ACM DL) BibTeX
- Kun Zhang, Laiwan Chan:
Nonlinear independent component analysis with minimal nonlinear distortion.
1127-1134
Electronic Edition (ACM DL) BibTeX
- Wei Zhang, Xiangyang Xue, Zichen Sun, Yue-Fei Guo, Hong Lu:
Optimal dimensionality of metric space for classification.
1135-1142
Electronic Edition (ACM DL) BibTeX
- Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanathan:
Conditional random fields for multi-agent reinforcement learning.
1143-1150
Electronic Edition (ACM DL) BibTeX
- Zheng Zhao, Huan Liu:
Spectral feature selection for supervised and unsupervised learning.
1151-1157
Electronic Edition (ACM DL) BibTeX
- Dengyong Zhou, Christopher J. C. Burges:
Spectral clustering and transductive learning with multiple views.
1159-1166
Electronic Edition (ACM DL) BibTeX
- Zhi-Hua Zhou, Jun-Ming Xu:
On the relation between multi-instance learning and semi-supervised learning.
1167-1174
Electronic Edition (ACM DL) BibTeX
- Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen:
Dynamic hierarchical Markov random fields and their application to web data extraction.
1175-1182
Electronic Edition (ACM DL) BibTeX
- Alexander Zien, Ulf Brefeld, Tobias Scheffer:
Transductive support vector machines for structured variables.
1183-1190
Electronic Edition (ACM DL) BibTeX
- Alexander Zien, Cheng Soon Ong:
Multiclass multiple kernel learning.
1191-1198
Electronic Edition (ACM DL) BibTeX
Copyright © Sat May 16 23:20:41 2009
by Michael Ley (ley@uni-trier.de)
