23. ICML 2006:
Pittsburgh,
Pennsylvania,
USA
William W. Cohen, Andrew Moore (Eds.):
Machine Learning, Proceedings of the Twenty-Third International Conference (ICML 2006), Pittsburgh, Pennsylvania, USA, June 25-29, 2006.
ACM International Conference Proceeding Series 148 ACM 2006, ISBN 1-59593-383-2 BibTeX
- Pieter Abbeel, Morgan Quigley, Andrew Y. Ng:
Using inaccurate models in reinforcement learning.
1-8
Electronic Edition (ACM DL) BibTeX
- Amit Agarwal, Elad Hazan, Satyen Kale, Robert E. Schapire:
Algorithms for portfolio management based on the Newton method.
9-16
Electronic Edition (ACM DL) BibTeX
- Sameer Agarwal, Kristin Branson, Serge Belongie:
Higher order learning with graphs.
17-24
Electronic Edition (ACM DL) BibTeX
- Shivani Agarwal:
Ranking on graph data.
25-32
Electronic Edition (ACM DL) BibTeX
- Cédric Archambeau, Nicolas Delannay, Michel Verleysen:
Robust probabilistic projections.
33-40
Electronic Edition (ACM DL) BibTeX
- Andreas Argyriou, Raphael Hauser, Charles A. Micchelli, Massimiliano Pontil:
A DC-programming algorithm for kernel selection.
41-48
Electronic Edition (ACM DL) BibTeX
- Nima Asgharbeygi, David J. Stracuzzi, Pat Langley:
Relational temporal difference learning.
49-56
Electronic Edition (ACM DL) BibTeX
- Arik Azran, Zoubin Ghahramani:
A new approach to data driven clustering.
57-64
Electronic Edition (ACM DL) BibTeX
- Maria-Florina Balcan, Alina Beygelzimer, John Langford:
Agnostic active learning.
65-72
Electronic Edition (ACM DL) BibTeX
- Maria-Florina Balcan, Avrim Blum:
On a theory of learning with similarity functions.
73-80
Electronic Edition (ACM DL) BibTeX
- Arindam Banerjee:
On Bayesian bounds.
81-88
Electronic Edition (ACM DL) BibTeX
- Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont, Georges Natsoulis:
Convex optimization techniques for fitting sparse Gaussian graphical models.
89-96
Electronic Edition (ACM DL) BibTeX
- Alina Beygelzimer, Sham Kakade, John Langford:
Cover trees for nearest neighbor.
97-104
Electronic Edition (ACM DL) BibTeX
- Ivona Bezáková, Adam Kalai, Rahul Santhanam:
Graph model selection using maximum likelihood.
105-112
Electronic Edition (ACM DL) BibTeX
- David M. Blei, John D. Lafferty:
Dynamic topic models.
113-120
Electronic Edition (ACM DL) BibTeX
- Edwin V. Bonilla, Christopher K. I. Williams, Felix V. Agakov, John Cavazos, John Thomson, Michael F. P. O'Boyle:
Predictive search distributions.
121-128
Electronic Edition (ACM DL) BibTeX
- Michael H. Bowling, Peter McCracken, Michael James, James Neufeld, Dana F. Wilkinson:
Learning predictive state representations using non-blind policies.
129-136
Electronic Edition (ACM DL) BibTeX
- Ulf Brefeld, Thomas Gärtner, Tobias Scheffer, Stefan Wrobel:
Efficient co-regularised least squares regression.
137-144
Electronic Edition (ACM DL) BibTeX
- Ulf Brefeld, Tobias Scheffer:
Semi-supervised learning for structured output variables.
145-152
Electronic Edition (ACM DL) BibTeX
- Miguel Á. Carreira-Perpiñán:
Fast nonparametric clustering with Gaussian blurring mean-shift.
153-160
Electronic Edition (ACM DL) BibTeX
- Rich Caruana, Alexandru Niculescu-Mizil:
An empirical comparison of supervised learning algorithms.
161-168
Electronic Edition (ACM DL) BibTeX
- Lawrence Cayton, Sanjoy Dasgupta:
Robust Euclidean embedding.
169-176
Electronic Edition (ACM DL) BibTeX
- Nicolò Cesa-Bianchi, Claudio Gentile, Luca Zaniboni:
Hierarchical classification: combining Bayes with SVM.
177-184
Electronic Edition (ACM DL) BibTeX
- Olivier Chapelle, Mingmin Chi, Alexander Zien:
A continuation method for semi-supervised SVMs.
185-192
Electronic Edition (ACM DL) BibTeX
- Pak-Ming Cheung, James T. Kwok:
A regularization framework for multiple-instance learning.
193-200
Electronic Edition (ACM DL) BibTeX
- Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou:
Trading convexity for scalability.
201-208
Electronic Edition (ACM DL) BibTeX
- Vincent Conitzer, Nikesh Garera:
Learning algorithms for online principal-agent problems (and selling goods online).
209-216
Electronic Edition (ACM DL) BibTeX
- Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel:
Dealing with non-stationary environments using context detection.
217-224
Electronic Edition (ACM DL) BibTeX
- Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwok:
Locally adaptive classification piloted by uncertainty.
225-232
Electronic Edition (ACM DL) BibTeX
- Jesse Davis, Mark Goadrich:
The relationship between Precision-Recall and ROC curves.
233-240
Electronic Edition (ACM DL) BibTeX
- Fernando De la Torre, Takeo Kanade:
Discriminative cluster analysis.
241-248
Electronic Edition (ACM DL) BibTeX
- Dennis DeCoste:
Collaborative prediction using ensembles of Maximum Margin Matrix Factorizations.
249-256
Electronic Edition (ACM DL) BibTeX
- Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin:
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems.
257-264
Electronic Edition (ACM DL) BibTeX
- François Denis, Christophe Nicolas Magnan, Liva Ralaivola:
Efficient learning of Naive Bayes classifiers under class-conditional classification noise.
265-272
Electronic Edition (ACM DL) BibTeX
- Marie desJardins, Eric Eaton, Kiri Wagstaff:
Learning user preferences for sets of objects.
273-280
Electronic Edition (ACM DL) BibTeX
- Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan Zha:
R1-PCA: rotational invariant L1-norm principal component analysis for robust subspace factorization.
281-288
Electronic Edition (ACM DL) BibTeX
- Charles Elkan:
Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution.
289-296
Electronic Edition (ACM DL) BibTeX
- Barbara E. Engelhardt, Michael I. Jordan, Steven E. Brenner:
A graphical model for predicting protein molecular function.
297-304
Electronic Edition (ACM DL) BibTeX
- Arkady Epshteyn, Gerald DeJong:
Qualitative reinforcement learning.
305-312
Electronic Edition (ACM DL) BibTeX
- Michael Fink, Shai Shalev-Shwartz, Yoram Singer, Shimon Ullman:
Online multiclass learning by interclass hypothesis sharing.
313-320
Electronic Edition (ACM DL) BibTeX
- Jochen Garcke:
Regression with the optimised combination technique.
321-328
Electronic Edition (ACM DL) BibTeX
- Yang Ge, Wenxin Jiang:
A note on mixtures of experts for multiclass responses: approximation rate and Consistent Bayesian Inference.
329-335
Electronic Edition (ACM DL) BibTeX
- Peter V. Gehler, Alex Holub, Max Welling:
The rate adapting poisson model for information retrieval and object recognition.
337-344
Electronic Edition (ACM DL) BibTeX
- Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc:
Kernelizing the output of tree-based methods.
345-352
Electronic Edition (ACM DL) BibTeX
- Amir Globerson, Sam T. Roweis:
Nightmare at test time: robust learning by feature deletion.
353-360
Electronic Edition (ACM DL) BibTeX
- Dilan Görür, Frank Jäkel, Carl Edward Rasmussen:
A choice model with infinitely many latent features.
361-368
Electronic Edition (ACM DL) BibTeX
- Alex Graves, Santiago Fernández, Faustino J. Gomez, Jürgen Schmidhuber:
Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks.
369-376
Electronic Edition (ACM DL) BibTeX
- Derek Greene, Padraig Cunningham:
Practical solutions to the problem of diagonal dominance in kernel document clustering.
377-384
Electronic Edition (ACM DL) BibTeX
- Patrick Haffner:
Fast transpose methods for kernel learning on sparse data.
385-392
Electronic Edition (ACM DL) BibTeX
- Steve Hanneke:
An analysis of graph cut size for transductive learning.
393-399
Electronic Edition (ACM DL) BibTeX
- Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall:
Learning a kernel function for classification with small training samples.
401-408
Electronic Edition (ACM DL) BibTeX
- Michael P. Holmes, Charles Lee Isbell Jr.:
Looping suffix tree-based inference of partially observable hidden state.
409-416
Electronic Edition (ACM DL) BibTeX
- Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu:
Batch mode active learning and its application to medical image classification.
417-424
Electronic Edition (ACM DL) BibTeX
- Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng:
Ranking individuals by group comparisons.
425-432
Electronic Edition (ACM DL) BibTeX
- Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rustandi:
Hidden process models.
433-440
Electronic Edition (ACM DL) BibTeX
- Brendan Juba:
Estimating relatedness via data compression.
441-448
Electronic Edition (ACM DL) BibTeX
- Philipp W. Keller, Shie Mannor, Doina Precup:
Automatic basis function construction for approximate dynamic programming and reinforcement learning.
449-456
Electronic Edition (ACM DL) BibTeX
- Wolf Kienzle, Kumar Chellapilla:
Personalized handwriting recognition via biased regularization.
457-464
Electronic Edition (ACM DL) BibTeX
- Seung-Jean Kim, Alessandro Magnani, Stephen P. Boyd:
Optimal kernel selection in Kernel Fisher discriminant analysis.
465-472
Electronic Edition (ACM DL) BibTeX
- Seung-Jean Kim, Alessandro Magnani, Sikandar Samar, Stephen P. Boyd, Johan Lim:
Pareto optimal linear classification.
473-480
Electronic Edition (ACM DL) BibTeX
- Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang:
Fast particle smoothing: if I had a million particles.
481-488
Electronic Edition (ACM DL) BibTeX
- George Konidaris, Andrew G. Barto:
Autonomous shaping: knowledge transfer in reinforcement learning.
489-496
Electronic Edition (ACM DL) BibTeX
- Andreas Krause, Jure Leskovec, Carlos Guestrin:
Data association for topic intensity tracking.
497-504
Electronic Edition (ACM DL) BibTeX
- Brian Kulis, Mátyás Sustik, Inderjit S. Dhillon:
Learning low-rank kernel matrices.
505-512
Electronic Edition (ACM DL) BibTeX
- Neil D. Lawrence, Joaquin Quiñonero Candela:
Local distance preservation in the GP-LVM through back constraints.
513-520
Electronic Edition (ACM DL) BibTeX
- Quoc V. Le, Alex J. Smola, Thomas Gärtner:
Simpler knowledge-based support vector machines.
521-528
Electronic Edition (ACM DL) BibTeX
- Chi-Hoon Lee, Russell Greiner, Shaojun Wang:
Using query-specific variance estimates to combine Bayesian classifiers.
529-536
Electronic Edition (ACM DL) BibTeX
- Alain Lehmann, John Shawe-Taylor:
A probabilistic model for text kernels.
537-544
Electronic Edition (ACM DL) BibTeX
- Marius Leordeanu, Martial Hebert:
Efficient MAP approximation for dense energy functions.
545-552
Electronic Edition (ACM DL) BibTeX
- Darrin P. Lewis, Tony Jebara, William Stafford Noble:
Nonstationary kernel combination.
553-560
Electronic Edition (ACM DL) BibTeX
- Hui Li, Xuejun Liao, Lawrence Carin:
Region-based value iteration for partially observable Markov decision processes.
561-568
Electronic Edition (ACM DL) BibTeX
- Ling Li:
Multiclass boosting with repartitioning.
569-576
Electronic Edition (ACM DL) BibTeX
- Wei Li, Andrew McCallum:
Pachinko allocation: DAG-structured mixture models of topic correlations.
577-584
Electronic Edition (ACM DL) BibTeX
- Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip S. Yu:
Spectral clustering for multi-type relational data.
585-592
Electronic Edition (ACM DL) BibTeX
- Le Lu, René Vidal:
Combined central and subspace clustering for computer vision applications.
593-600
Electronic Edition (ACM DL) BibTeX
- Mauro Maggioni, Sridhar Mahadevan:
Fast direct policy evaluation using multiscale analysis of Markov diffusion processes.
601-608
Electronic Edition (ACM DL) BibTeX
- Gonzalo Martínez-Muñoz, Alberto Suárez:
Pruning in ordered bagging ensembles.
609-616
Electronic Edition (ACM DL) BibTeX
- Julian John McAuley, Tibério S. Caetano, Alex J. Smola, Matthias O. Franz:
Learning high-order MRF priors of color images.
617-624
Electronic Edition (ACM DL) BibTeX
- Marina Meila:
The uniqueness of a good optimum for K-means.
625-632
Electronic Edition (ACM DL) BibTeX
- Roland Memisevic:
Kernel information embeddings.
633-640
Electronic Edition (ACM DL) BibTeX
- Baback Moghaddam, Yair Weiss, Shai Avidan:
Generalized spectral bounds for sparse LDA.
641-648
Electronic Edition (ACM DL) BibTeX
- Moni Naor, Guy N. Rothblum:
Learning to impersonate.
649-656
Electronic Edition (ACM DL) BibTeX
- Mukund Narasimhan, Paul A. Viola, Michael Shilman:
Online decoding of Markov models under latency constraints.
657-664
Electronic Edition (ACM DL) BibTeX
- Negin Nejati, Pat Langley, Tolga Könik:
Learning hierarchical task networks by observation.
665-672
Electronic Edition (ACM DL) BibTeX
- Yuriy Nevmyvaka, Yi Feng, Michael S. Kearns:
Reinforcement learning for optimized trade execution.
673-680
Electronic Edition (ACM DL) BibTeX
- Navneet Panda, Edward Y. Chang, Gang Wu:
Concept boundary detection for speeding up SVMs.
681-688
Electronic Edition (ACM DL) BibTeX
- Francisco Pereira, Geoffrey J. Gordon:
The support vector decomposition machine.
689-696
Electronic Edition (ACM DL) BibTeX
- Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevin Regan:
An analytic solution to discrete Bayesian reinforcement learning.
697-704
Electronic Edition (ACM DL) BibTeX
- Rouhollah Rahmani, Sally A. Goldman:
MISSL: multiple-instance semi-supervised learning.
705-712
Electronic Edition (ACM DL) BibTeX
- Rajat Raina, Andrew Y. Ng, Daphne Koller:
Constructing informative priors using transfer learning.
713-720
Electronic Edition (ACM DL) BibTeX
- Liva Ralaivola, François Denis, Christophe Nicolas Magnan:
CN = CPCN.
721-728
Electronic Edition (ACM DL) BibTeX
- Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinkevich:
Maximum margin planning.
729-736
Electronic Edition (ACM DL) BibTeX
- Pradeep D. Ravikumar, John D. Lafferty:
Quadratic programming relaxations for metric labeling and Markov random field MAP estimation.
737-744
Electronic Edition (ACM DL) BibTeX
- Jean-Michel Renders, Éric Gaussier, Cyril Goutte, François Pacull, Gabriela Csurka:
Categorization in multiple category systems.
745-752
Electronic Edition (ACM DL) BibTeX
- Lev Reyzin, Robert E. Schapire:
How boosting the margin can also boost classifier complexity.
753-760
Electronic Edition (ACM DL) BibTeX
- David A. Ross, Simon Osindero, Richard S. Zemel:
Combining discriminative features to infer complex trajectories.
761-768
Electronic Edition (ACM DL) BibTeX
- Josep Roure, Andrew W. Moore:
Sequential update of ADtrees.
769-776
Electronic Edition (ACM DL) BibTeX
- Matthew R. Rudary, Satinder P. Singh:
Predictive linear-Gaussian models of controlled stochastic dynamical systems.
777-784
Electronic Edition (ACM DL) BibTeX
- Ulrich Rückert, Stefan Kramer:
A statistical approach to rule learning.
785-792
Electronic Edition (ACM DL) BibTeX
- Sunita Sarawagi:
Efficient inference on sequence segmentation models.
793-800
Electronic Edition (ACM DL) BibTeX
- Prithviraj Sen, Lise Getoor:
Cost-sensitive learning with conditional Markov networks.
801-808
Electronic Edition (ACM DL) BibTeX
- Victor S. Sheng, Charles X. Ling:
Feature value acquisition in testing: a sequential batch test algorithm.
809-816
Electronic Edition (ACM DL) BibTeX
- Pannagadatta K. Shivaswamy, Tony Jebara:
Permutation invariant SVMs.
817-824
Electronic Edition (ACM DL) BibTeX
- Ricardo Silva, Richard Scheines:
Bayesian learning of measurement and structural models.
825-832
Electronic Edition (ACM DL) BibTeX
- Özgür Simsek, Andrew G. Barto:
An intrinsic reward mechanism for efficient exploration.
833-840
Electronic Edition (ACM DL) BibTeX
- Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chapelle:
Deterministic annealing for semi-supervised kernel machines.
841-848
Electronic Edition (ACM DL) BibTeX
- Surendra K. Singhi, Huan Liu:
Feature subset selection bias for classification learning.
849-856
Electronic Edition (ACM DL) BibTeX
- Le Song, Julien Epps:
Classifying EEG for brain-computer interfaces: learning optimal filters for dynamical system features.
857-864
Electronic Edition (ACM DL) BibTeX
- Nathan Srebro, Gregory Shakhnarovich, Sam T. Roweis:
An investigation of computational and informational limits in Gaussian mixture clustering.
865-872
Electronic Edition (ACM DL) BibTeX
- David H. Stern, Ralf Herbrich, Thore Graepel:
Bayesian pattern ranking for move prediction in the game of Go.
873-880
Electronic Edition (ACM DL) BibTeX
- Alexander L. Strehl, Lihong Li, Eric Wiewiora, John Langford, Michael L. Littman:
PAC model-free reinforcement learning.
881-888
Electronic Edition (ACM DL) BibTeX
- Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh:
Experience-efficient learning in associative bandit problems.
889-896
Electronic Edition (ACM DL) BibTeX
- Jiang Su, Harry Zhang:
Full Bayesian network classifiers.
897-904
Electronic Edition (ACM DL) BibTeX
- Masashi Sugiyama:
Local Fisher discriminant analysis for supervised dimensionality reduction.
905-912
Electronic Edition (ACM DL) BibTeX
- Yijun Sun, Jian Li:
Iterative RELIEF for feature weighting.
913-920
Electronic Edition (ACM DL) BibTeX
- Benyang Tang, Dominic Mazzoni:
Multiclass reduced-set support vector machines.
921-928
Electronic Edition (ACM DL) BibTeX
- Choon Hui Teo, S. V. N. Vishwanathan:
Fast and space efficient string kernels using suffix arrays.
929-936
Electronic Edition (ACM DL) BibTeX
- Jo-Anne Ting, Aaron D'Souza, Stefan Schaal:
Bayesian regression with input noise for high dimensional data.
937-944
Electronic Edition (ACM DL) BibTeX
- Marc Toussaint, Amos J. Storkey:
Probabilistic inference for solving discrete and continuous state Markov Decision Processes.
945-952
Electronic Edition (ACM DL) BibTeX
- Koji Tsuda, Taku Kudo:
Clustering graphs by weighted substructure mining.
953-960
Electronic Edition (ACM DL) BibTeX
- Sriharsha Veeramachaneni, Emanuele Olivetti, Paolo Avesani:
Active sampling for detecting irrelevant features.
961-968
Electronic Edition (ACM DL) BibTeX
- S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy:
Accelerated training of conditional random fields with stochastic gradient methods.
969-976
Electronic Edition (ACM DL) BibTeX
- Hanna M. Wallach:
Topic modeling: beyond bag-of-words.
977-984
Electronic Edition (ACM DL) BibTeX
- Fei Wang, Changshui Zhang:
Label propagation through linear neighborhoods.
985-992
Electronic Edition (ACM DL) BibTeX
- Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky:
Two-dimensional solution path for support vector regression.
993-1000
Electronic Edition (ACM DL) BibTeX
- Manfred K. Warmuth, Jun Liao, Gunnar Rätsch:
Totally corrective boosting algorithms that maximize the margin.
1001-1008
Electronic Edition (ACM DL) BibTeX
- Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik:
Inference with the Universum.
1009-1016
Electronic Edition (ACM DL) BibTeX
- David Wingate, Satinder P. Singh:
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems.
1017-1024
Electronic Edition (ACM DL) BibTeX
- Britton Wolfe, Satinder P. Singh:
Predictive state representations with options.
1025-1032
Electronic Edition (ACM DL) BibTeX
- Xiaopeng Xi, Eamonn J. Keogh, Christian R. Shelton, Li Wei, Chotirat Ann Ratanamahatana:
Fast time series classification using numerosity reduction.
1033-1040
Electronic Edition (ACM DL) BibTeX
- Lin Xiao, Jun Sun, Stephen P. Boyd:
A duality view of spectral methods for dimensionality reduction.
1041-1048
Electronic Edition (ACM DL) BibTeX
- Eric P. Xing, Kyung-Ah Sohn, Michael I. Jordan, Yee Whye Teh:
Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture.
1049-1056
Electronic Edition (ACM DL) BibTeX
- Linli Xu, Dana F. Wilkinson, Finnegan Southey, Dale Schuurmans:
Discriminative unsupervised learning of structured predictors.
1057-1064
Electronic Edition (ACM DL) BibTeX
- Xin Yang, Haoying Fu, Hongyuan Zha, Jesse L. Barlow:
Semi-supervised nonlinear dimensionality reduction.
1065-1072
Electronic Edition (ACM DL) BibTeX
- Jieping Ye, Tao Xiong:
Null space versus orthogonal linear discriminant analysis.
1073-1080
Electronic Edition (ACM DL) BibTeX
- Kai Yu, Jinbo Bi, Volker Tresp:
Active learning via transductive experimental design.
1081-1088
Electronic Edition (ACM DL) BibTeX
- Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel:
Collaborative ordinal regression.
1089-1096
Electronic Edition (ACM DL) BibTeX
- Kai Zhang, James T. Kwok:
Block-quantized kernel matrix for fast spectral embedding.
1097-1104
Electronic Edition (ACM DL) BibTeX
- Alice X. Zheng, Michael I. Jordan, Ben Liblit, Mayur Naik, Alex Aiken:
Statistical debugging: simultaneous identification of multiple bugs.
1105-1112
Electronic Edition (ACM DL) BibTeX
- Fei Zheng, Geoffrey I. Webb:
Efficient lazy elimination for averaged one-dependence estimators.
1113-1120
Electronic Edition (ACM DL) BibTeX
Copyright © Sat May 16 23:20:41 2009
by Michael Ley (ley@uni-trier.de)
