25. ICML 2008:
Helsinki,
Finland
William W. Cohen, Andrew McCallum, Sam T. Roweis (Eds.):
Machine Learning, Proceedings of the Twenty-Fifth International Conference (ICML 2008), Helsinki, Finland, June 5-9, 2008.
ACM International Conference Proceeding Series 307 ACM 2008, ISBN 978-1-60558-205-4 BibTeX
- Ryan Prescott Adams, Oliver Stegle:
Gaussian process product models for nonparametric nonstationarity.
1-8
Electronic Edition (ACM DL) BibTeX
- Cyril Allauzen, Mehryar Mohri, Ameet Talwalkar:
Sequence kernels for predicting protein essentiality.
9-16
Electronic Edition (ACM DL) BibTeX
- Qi An, Chunping Wang, Ivo Shterev, Eric Wang, Lawrence Carin, David B. Dunson:
Hierarchical kernel stick-breaking process for multi-task image analysis.
17-24
Electronic Edition (ACM DL) BibTeX
- Francis R. Bach:
Graph kernels between point clouds.
25-32
Electronic Edition (ACM DL) BibTeX
- Francis R. Bach:
Bolasso: model consistent Lasso estimation through the bootstrap.
33-40
Electronic Edition (ACM DL) BibTeX
- Leon Barrett, Srini Narayanan:
Learning all optimal policies with multiple criteria.
41-47
Electronic Edition (ACM DL) BibTeX
- Charles Bergeron, Jed Zaretzki, Curt M. Breneman, Kristin P. Bennett:
Multiple instance ranking.
48-55
Electronic Edition (ACM DL) BibTeX
- Steffen Bickel, Jasmina Bogojeska, Thomas Lengauer, Tobias Scheffer:
Multi-task learning for HIV therapy screening.
56-63
Electronic Edition (ACM DL) BibTeX
- Michael Biggs, Ali Ghodsi, Stephen A. Vavasis:
Nonnegative matrix factorization via rank-one downdate.
64-71
Electronic Edition (ACM DL) BibTeX
- Michael H. Bowling, Michael Johanson, Neil Burch, Duane Szafron:
Strategy evaluation in extensive games with importance sampling.
72-79
Electronic Edition (ACM DL) BibTeX
- Brent Bryan, Jeff G. Schneider:
Actively learning level-sets of composite functions.
80-87
Electronic Edition (ACM DL) BibTeX
- Francois Caron, Arnaud Doucet:
Sparse Bayesian nonparametric regression.
88-95
Electronic Edition (ACM DL) BibTeX
- Rich Caruana, Nikolaos Karampatziakis, Ainur Yessenalina:
An empirical evaluation of supervised learning in high dimensions.
96-103
Electronic Edition (ACM DL) BibTeX
- Bryan C. Catanzaro, Narayanan Sundaram, Kurt Keutzer:
Fast support vector machine training and classification on graphics processors.
104-111
Electronic Edition (ACM DL) BibTeX
- Lawrence Cayton:
Fast nearest neighbor retrieval for bregman divergences.
112-119
Electronic Edition (ACM DL) BibTeX
- Hakan Cevikalp, Bill Triggs, Robi Polikar:
Nearest hyperdisk methods for high-dimensional classification.
120-127
Electronic Edition (ACM DL) BibTeX
- David L. Chen, Raymond J. Mooney:
Learning to sportscast: a test of grounded language acquisition.
128-135
Electronic Edition (ACM DL) BibTeX
- Jianhui Chen, Jieping Ye:
Training SVM with indefinite kernels.
136-143
Electronic Edition (ACM DL) BibTeX
- Adam Coates, Pieter Abbeel, Andrew Y. Ng:
Learning for control from multiple demonstrations.
144-151
Electronic Edition (ACM DL) BibTeX
- Tom Coleman, James Saunderson, Anthony Wirth:
Spectral clustering with inconsistent advice.
152-159
Electronic Edition (ACM DL) BibTeX
- Ronan Collobert, Jason Weston:
A unified architecture for natural language processing: deep neural networks with multitask learning.
160-167
Electronic Edition (ACM DL) BibTeX
- Andrés Corrada-Emmanuel, Howard J. Schultz:
Autonomous geometric precision error estimation in low-level computer vision tasks.
168-175
Electronic Edition (ACM DL) BibTeX
- Corinna Cortes, Mehryar Mohri, Dmitry Pechyony, Ashish Rastogi:
Stability of transductive regression algorithms.
176-183
Electronic Edition (ACM DL) BibTeX
- Koby Crammer, Partha Pratim Talukdar, Fernando Pereira:
A rate-distortion one-class model and its applications to clustering.
184-191
Electronic Edition (ACM DL) BibTeX
- John P. Cunningham, Krishna V. Shenoy, Maneesh Sahani:
Fast Gaussian process methods for point process intensity estimation.
192-199
Electronic Edition (ACM DL) BibTeX
- Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu:
Self-taught clustering.
200-207
Electronic Edition (ACM DL) BibTeX
- Sanjoy Dasgupta, Daniel Hsu:
Hierarchical sampling for active learning.
208-215
Electronic Edition (ACM DL) BibTeX
- Ofer Dekel, Ohad Shamir:
Learning to classify with missing and corrupted features.
216-223
Electronic Edition (ACM DL) BibTeX
- Krzysztof Dembczynski, Wojciech Kotlowski, Roman Slowinski:
Maximum likelihood rule ensembles.
224-231
Electronic Edition (ACM DL) BibTeX
- Uwe Dick, Peter Haider, Tobias Scheffer:
Learning from incomplete data with infinite imputations.
232-239
Electronic Edition (ACM DL) BibTeX
- Carlos Diuk, Andre Cohen, Michael L. Littman:
An object-oriented representation for efficient reinforcement learning.
240-247
Electronic Edition (ACM DL) BibTeX
- Pinar Donmez, Jaime G. Carbonell:
Optimizing estimated loss reduction for active sampling in rank learning.
248-255
Electronic Edition (ACM DL) BibTeX
- Finale Doshi, Joelle Pineau, Nicholas Roy:
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs.
256-263
Electronic Edition (ACM DL) BibTeX
- Mark Dredze, Koby Crammer, Fernando Pereira:
Confidence-weighted linear classification.
264-271
Electronic Edition (ACM DL) BibTeX
- John Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra:
Efficient projections onto the l1-ball for learning in high dimensions.
272-279
Electronic Edition (ACM DL) BibTeX
- Charles Dugas, David Gadoury:
Pointwise exact bootstrap distributions of cost curves.
280-287
Electronic Edition (ACM DL) BibTeX
- Murat Dundar, Matthias Wolf, Sarang Lakare, Marcos Salganicoff, Vikas C. Raykar:
Polyhedral classifier for target detection: a case study: colorectal cancer.
288-295
Electronic Edition (ACM DL) BibTeX
- Arkady Epshteyn, Adam Vogel, Gerald DeJong:
Active reinforcement learning.
296-303
Electronic Edition (ACM DL) BibTeX
- Thomas Finley, Thorsten Joachims:
Training structural SVMs when exact inference is intractable.
304-311
Electronic Edition (ACM DL) BibTeX
- Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
An HDP-HMM for systems with state persistence.
312-319
Electronic Edition (ACM DL) BibTeX
- Vojtech Franc, Sören Sonnenburg:
Optimized cutting plane algorithm for support vector machines.
320-327
Electronic Edition (ACM DL) BibTeX
- Vojtech Franc, Pavel Laskov, Klaus-Robert Müller:
Stopping conditions for exact computation of leave-one-out error in support vector machines.
328-335
Electronic Edition (ACM DL) BibTeX
- Jordan Frank, Shie Mannor, Doina Precup:
Reinforcement learning in the presence of rare events.
336-343
Electronic Edition (ACM DL) BibTeX
- Ryan Gomes, Max Welling, Pietro Perona:
Memory bounded inference in topic models.
344-351
Electronic Edition (ACM DL) BibTeX
- Mehmet Gönen, Ethem Alpaydin:
Localized multiple kernel learning.
352-359
Electronic Edition (ACM DL) BibTeX
- Geoffrey J. Gordon, Amy R. Greenwald, Casey Marks:
No-regret learning in convex games.
360-367
Electronic Edition (ACM DL) BibTeX
- Gholamreza Haffari, Yang Wang, Shaojun Wang, Greg Mori, Feng Jiao:
Boosting with incomplete information.
368-375
Electronic Edition (ACM DL) BibTeX
- Jihun Ham, Daniel D. Lee:
Grassmann discriminant analysis: a unifying view on subspace-based learning.
376-383
Electronic Edition (ACM DL) BibTeX
- Georg Heigold, Thomas Deselaers, Ralf Schlüter, Hermann Ney:
Modified MMI/MPE: a direct evaluation of the margin in speech recognition.
384-391
Electronic Edition (ACM DL) BibTeX
- Katherine A. Heller, Sinead Williamson, Zoubin Ghahramani:
Statistical models for partial membership.
392-399
Electronic Edition (ACM DL) BibTeX
- Steven C. H. Hoi, Rong Jin:
Active kernel learning.
400-407
Electronic Edition (ACM DL) BibTeX
- Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan:
A dual coordinate descent method for large-scale linear SVM.
408-415
Electronic Edition (ACM DL) BibTeX
- Tuyen N. Huynh, Raymond J. Mooney:
Discriminative structure and parameter learning for Markov logic networks.
416-423
Electronic Edition (ACM DL) BibTeX
- Aapo Hyvärinen, Shohei Shimizu, Patrik O. Hoyer:
Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity.
424-431
Electronic Edition (ACM DL) BibTeX
- Sham M. Kakade, Shai Shalev-Shwartz, Ambuj Tewari:
Efficient bandit algorithms for online multiclass prediction.
440-447
Electronic Edition (ACM DL) BibTeX
- Michael Karlen, Jason Weston, Ayse Erkan, Ronan Collobert:
Large scale manifold transduction.
448-455
Electronic Edition (ACM DL) BibTeX
- Kristian Kersting, Kurt Driessens:
Non-parametric policy gradients: a unified treatment of propositional and relational domains.
456-463
Electronic Edition (ACM DL) BibTeX
- Sergey Kirshner, Barnabás Póczos:
ICA and ISA using Schweizer-Wolff measure of dependence.
464-471
Electronic Edition (ACM DL) BibTeX
- Alexandre Klementiev, Dan Roth, Kevin Small:
Unsupervised rank aggregation with distance-based models.
472-479
Electronic Edition (ACM DL) BibTeX
- Pushmeet Kohli, Alexander Shekhovtsov, Carsten Rother, Vladimir Kolmogorov, Philip H. S. Torr:
On partial optimality in multi-label MRFs.
480-487
Electronic Edition (ACM DL) BibTeX
- J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, Charles DuHadway:
Space-indexed dynamic programming: learning to follow trajectories.
488-495
Electronic Edition (ACM DL) BibTeX
- Risi Imre Kondor, Karsten M. Borgwardt:
The skew spectrum of graphs.
496-503
Electronic Edition (ACM DL) BibTeX
- Ondrej Kuzelka, Filip Zelezný:
Fast estimation of first-order clause coverage through randomization and maximum likelihood.
504-511
Electronic Edition (ACM DL) BibTeX
- Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li:
Query-level stability and generalization in learning to rank.
512-519
Electronic Edition (ACM DL) BibTeX
- Niels Landwehr:
Modeling interleaved hidden processes.
520-527
Electronic Edition (ACM DL) BibTeX
- John Langford, Alexander L. Strehl, Jennifer Wortman:
Exploration scavenging.
528-535
Electronic Edition (ACM DL) BibTeX
- Hugo Larochelle, Yoshua Bengio:
Classification using discriminative restricted Boltzmann machines.
536-543
Electronic Edition (ACM DL) BibTeX
- Alessandro Lazaric, Marcello Restelli, Andrea Bonarini:
Transfer of samples in batch reinforcement learning.
544-551
Electronic Edition (ACM DL) BibTeX
- Guy Lebanon, Yang Zhao:
Local likelihood modeling of temporal text streams.
552-559
Electronic Edition (ACM DL) BibTeX
- Lihong Li:
A worst-case comparison between temporal difference and residual gradient with linear function approximation.
560-567
Electronic Edition (ACM DL) BibTeX
- Lihong Li, Michael L. Littman, Thomas J. Walsh:
Knows what it knows: a framework for self-aware learning.
568-575
Electronic Edition (ACM DL) BibTeX
- Zhenguo Li, Jianzhuang Liu, Xiaoou Tang:
Pairwise constraint propagation by semidefinite programming for semi-supervised classification.
576-583
Electronic Edition (ACM DL) BibTeX
- Percy Liang, Michael I. Jordan:
An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators.
584-591
Electronic Edition (ACM DL) BibTeX
- Percy Liang, Hal Daumé III, Dan Klein:
Structure compilation: trading structure for features.
592-599
Electronic Edition (ACM DL) BibTeX
- Nicolas Loeff, David A. Forsyth, Deepak Ramachandran:
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning.
600-607
Electronic Edition (ACM DL) BibTeX
- Philip M. Long, Rocco A. Servedio:
Random classification noise defeats all convex potential boosters.
608-615
Electronic Edition (ACM DL) BibTeX
- Haiping Lu, Konstantinos N. Plataniotis, Anastasios N. Venetsanopoulos:
Uncorrelated multilinear principal component analysis through successive variance maximization.
616-623
Electronic Edition (ACM DL) BibTeX
- Zhengdong Lu, Todd K. Leen, Yonghong Huang, Deniz Erdogmus:
A reproducing kernel Hilbert space framework for pairwise time series distances.
624-631
Electronic Edition (ACM DL) BibTeX
- Takaki Makino, Toshihisa Takagi:
On-line discovery of temporal-difference networks.
632-639
Electronic Edition (ACM DL) BibTeX
- André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing:
Nonextensive entropic kernels.
640-647
Electronic Edition (ACM DL) BibTeX
- Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich:
Automatic discovery and transfer of MAXQ hierarchies.
648-655
Electronic Edition (ACM DL) BibTeX
- Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon:
Rank minimization via online learning.
656-663
Electronic Edition (ACM DL) BibTeX
- Francisco S. Melo, Sean P. Meyn, M. Isabel Ribeiro:
An analysis of reinforcement learning with function approximation.
664-671
Electronic Edition (ACM DL) BibTeX
- Volodymyr Mnih, Csaba Szepesvári, Jean-Yves Audibert:
Empirical Bernstein stopping.
672-679
Electronic Edition (ACM DL) BibTeX
- M. Pawan Kumar, Philip H. S. Torr:
Efficiently solving convex relaxations for MAP estimation.
680-687
Electronic Edition (ACM DL) BibTeX
- Shravan Matthur Narayanamurthy, Balaraman Ravindran:
On the hardness of finding symmetries in Markov decision processes.
688-695
Electronic Edition (ACM DL) BibTeX
- Siegfried Nijssen:
Bayes optimal classification for decision trees.
696-703
Electronic Edition (ACM DL) BibTeX
- Sebastian Nowozin, Gökhan H. Bakir:
A decoupled approach to exemplar-based unsupervised learning.
704-711
Electronic Edition (ACM DL) BibTeX
- Deirdre B. O'Brien, Maya R. Gupta, Robert M. Gray:
Cost-sensitive multi-class classification from probability estimates.
712-719
Electronic Edition (ACM DL) BibTeX
- Francesco Orabona, Joseph Keshet, Barbara Caputo:
The projectron: a bounded kernel-based Perceptron.
720-727
Electronic Edition (ACM DL) BibTeX
- Hua Ouyang, Alex Gray:
Learning dissimilarities by ranking: from SDP to QP.
728-735
Electronic Edition (ACM DL) BibTeX
- Jean-François Paiement, Yves Grandvalet, Samy Bengio, Douglas Eck:
A distance model for rhythms.
736-743
Electronic Edition (ACM DL) BibTeX
- Mark Palatucci, Andrew Carlson:
On the chance accuracies of large collections of classifiers.
744-751
Electronic Edition (ACM DL) BibTeX
- Ronald Parr, Lihong Li, Gavin Taylor, Christopher Painter-Wakefield, Michael L. Littman:
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning.
752-759
Electronic Edition (ACM DL) BibTeX
- Kai Puolamäki, Antti Ajanki, Samuel Kaski:
Learning to learn implicit queries from gaze patterns.
760-767
Electronic Edition (ACM DL) BibTeX
- Yuting Qi, Dehong Liu, David B. Dunson, Lawrence Carin:
Multi-task compressive sensing with Dirichlet process priors.
768-775
Electronic Edition (ACM DL) BibTeX
- Novi Quadrianto, Alex J. Smola, Tibério S. Caetano, Quoc V. Le:
Estimating labels from label proportions.
776-783
Electronic Edition (ACM DL) BibTeX
- Filip Radlinski, Robert Kleinberg, Thorsten Joachims:
Learning diverse rankings with multi-armed bandits.
784-791
Electronic Edition (ACM DL) BibTeX
- Marc'Aurelio Ranzato, Martin Szummer:
Semi-supervised learning of compact document representations with deep networks.
792-799
Electronic Edition (ACM DL) BibTeX
- Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwright:
Message-passing for graph-structured linear programs: proximal projections, convergence and rounding schemes.
800-807
Electronic Edition (ACM DL) BibTeX
- Vikas C. Raykar, Balaji Krishnapuram, Jinbo Bi, Murat Dundar, R. Bharat Rao:
Bayesian multiple instance learning: automatic feature selection and inductive transfer.
808-815
Electronic Edition (ACM DL) BibTeX
- Joseph Reisinger, Peter Stone, Risto Miikkulainen:
Online kernel selection for Bayesian reinforcement learning.
816-823
Electronic Edition (ACM DL) BibTeX
- Lu Ren, David B. Dunson, Lawrence Carin:
The dynamic hierarchical Dirichlet process.
824-831
Electronic Edition (ACM DL) BibTeX
- Irina Rish, Genady Grabarnik, Guillermo Cecchi, Francisco Pereira, Geoffrey J. Gordon:
Closed-form supervised dimensionality reduction with generalized linear models.
832-839
Electronic Edition (ACM DL) BibTeX
- Saharon Rosset:
Bi-level path following for cross validated solution of kernel quantile regression.
840-847
Electronic Edition (ACM DL) BibTeX
- Volker Roth, Bernd Fischer:
The Group-Lasso for generalized linear models: uniqueness of solutions and efficient algorithms.
848-855
Electronic Edition (ACM DL) BibTeX
- Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabarisoa, Renaud Keriven:
Robust matching and recognition using context-dependent kernels.
856-863
Electronic Edition (ACM DL) BibTeX
- Jun Sakuma, Shigenobu Kobayashi, Rebecca N. Wright:
Privacy-preserving reinforcement learning.
864-871
Electronic Edition (ACM DL) BibTeX
- Ruslan Salakhutdinov, Iain Murray:
On the quantitative analysis of deep belief networks.
872-879
Electronic Edition (ACM DL) BibTeX
- Ruslan Salakhutdinov, Andriy Mnih:
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo.
880-887
Electronic Edition (ACM DL) BibTeX
- Sunita Sarawagi, Rahul Gupta:
Accurate max-margin training for structured output spaces.
888-895
Electronic Edition (ACM DL) BibTeX
- Purnamrita Sarkar, Andrew W. Moore, Amit Prakash:
Fast incremental proximity search in large graphs.
896-903
Electronic Edition (ACM DL) BibTeX
- Michael Schnall-Levin, Leonid Chindelevitch, Bonnie Berger:
Inverting the Viterbi algorithm: an abstract framework for structure design.
904-911
Electronic Edition (ACM DL) BibTeX
- Matthias W. Seeger, Hannes Nickisch:
Compressed sensing and Bayesian experimental design.
912-919
Electronic Edition (ACM DL) BibTeX
- Yevgeny Seldin, Naftali Tishby:
Multi-classification by categorical features via clustering.
920-927
Electronic Edition (ACM DL) BibTeX
- Shai Shalev-Shwartz, Nathan Srebro:
SVM optimization: inverse dependence on training set size.
928-935
Electronic Edition (ACM DL) BibTeX
- Tao Shi, Mikhail Belkin, Bin Yu:
Data spectroscopy: learning mixture models using eigenspaces of convolution operators.
936-943
Electronic Edition (ACM DL) BibTeX
- Kilho Shin, Tetsuji Kuboyama:
A generalization of Haussler's convolution kernel: mapping kernel.
944-951
Electronic Edition (ACM DL) BibTeX
- Suyash Shringarpure, Eric P. Xing:
mStruct: a new admixture model for inference of population structure in light of both genetic admixing and allele mutations.
952-959
Electronic Edition (ACM DL) BibTeX
- Christian D. Sigg, Joachim M. Buhmann:
Expectation-maximization for sparse and non-negative PCA.
960-967
Electronic Edition (ACM DL) BibTeX
- David Silver, Richard S. Sutton, Martin Müller:
Sample-based learning and search with permanent and transient memories.
968-975
Electronic Edition (ACM DL) BibTeX
- Vikas Sindhwani, David S. Rosenberg:
An RKHS for multi-view learning and manifold co-regularization.
976-983
Electronic Edition (ACM DL) BibTeX
- Nataliya Sokolovska, Olivier Cappé, François Yvon:
The asymptotics of semi-supervised learning in discriminative probabilistic models.
984-991
Electronic Edition (ACM DL) BibTeX
- Le Song, Xinhua Zhang, Alex J. Smola, Arthur Gretton, Bernhard Schölkopf:
Tailoring density estimation via reproducing kernel moment matching.
992-999
Electronic Edition (ACM DL) BibTeX
- Daria Sorokina, Rich Caruana, Mirek Riedewald, Daniel Fink:
Detecting statistical interactions with additive groves of trees.
1000-1007
Electronic Edition (ACM DL) BibTeX
- Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G. Lanckriet:
Metric embedding for kernel classification rules.
1008-1015
Electronic Edition (ACM DL) BibTeX
- Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwin:
Discriminative parameter learning for Bayesian networks.
1016-1023
Electronic Edition (ACM DL) BibTeX
- Liang Sun, Shuiwang Ji, Jieping Ye:
A least squares formulation for canonical correlation analysis.
1024-1031
Electronic Edition (ACM DL) BibTeX
- Umar Syed, Michael H. Bowling, Robert E. Schapire:
Apprenticeship learning using linear programming.
1032-1039
Electronic Edition (ACM DL) BibTeX
- Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy:
Composite kernel learning.
1040-1047
Electronic Edition (ACM DL) BibTeX
- Istvan Szita, András Lörincz:
The many faces of optimism: a unifying approach.
1048-1055
Electronic Edition (ACM DL) BibTeX
- Akiko Takeda, Masashi Sugiyama:
nu-support vector machine as conditional value-at-risk minimization.
1056-1063
Electronic Edition (ACM DL) BibTeX
- Tijmen Tieleman:
Training restricted Boltzmann machines using approximations to the likelihood gradient.
1064-1071
Electronic Edition (ACM DL) BibTeX
- Tsuyoshi Ueno, Motoaki Kawanabe, Takeshi Mori, Shin-ichi Maeda, Shin Ishii:
A semiparametric statistical approach to model-free policy evaluation.
1072-1079
Electronic Edition (ACM DL) BibTeX
- Raquel Urtasun, David J. Fleet, Andreas Geiger, Jovan Popovic, Trevor Darrell, Neil D. Lawrence:
Topologically-constrained latent variable models.
1080-1087
Electronic Edition (ACM DL) BibTeX
- Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubin Ghahramani:
Beam sampling for the infinite hidden Markov model.
1088-1095
Electronic Edition (ACM DL) BibTeX
- Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol:
Extracting and composing robust features with denoising autoencoders.
1096-1103
Electronic Edition (ACM DL) BibTeX
- Vladimir Vovk, Fedor Zhdanov:
Prediction with expert advice for the Brier game.
1104-1111
Electronic Edition (ACM DL) BibTeX
- Christian Walder, Kwang In Kim, Bernhard Schölkopf:
Sparse multiscale gaussian process regression.
1112-1119
Electronic Edition (ACM DL) BibTeX
- Chang Wang, Sridhar Mahadevan:
Manifold alignment using Procrustes analysis.
1120-1127
Electronic Edition (ACM DL) BibTeX
- Hua-Yan Wang, Qiang Yang, Hong Qin, Hongbin Zha:
Dirichlet component analysis: feature extraction for compositional data.
1128-1135
Electronic Edition (ACM DL) BibTeX
- Hua-Yan Wang, Qiang Yang, Hongbin Zha:
Adaptive p-posterior mixture-model kernels for multiple instance learning.
1136-1143
Electronic Edition (ACM DL) BibTeX
- Jun Wang, Tony Jebara, Shih-Fu Chang:
Graph transduction via alternating minimization.
1144-1151
Electronic Edition (ACM DL) BibTeX
- Wei Wang, Zhi-Hua Zhou:
On multi-view active learning and the combination with semi-supervised learning.
1152-1159
Electronic Edition (ACM DL) BibTeX
- Kilian Q. Weinberger, Lawrence K. Saul:
Fast solvers and efficient implementations for distance metric learning.
1160-1167
Electronic Edition (ACM DL) BibTeX
- Jason Weston, Frédéric Ratle, Ronan Collobert:
Deep learning via semi-supervised embedding.
1168-1175
Electronic Edition (ACM DL) BibTeX
- David Wingate, Satinder P. Singh:
Efficiently learning linear-linear exponential family predictive representations of state.
1176-1183
Electronic Edition (ACM DL) BibTeX
- Jason Wolfe, Aria Haghighi, Dan Klein:
Fully distributed EM for very large datasets.
1184-1191
Electronic Edition (ACM DL) BibTeX
- Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, Hang Li:
Listwise approach to learning to rank: theory and algorithm.
1192-1199
Electronic Edition (ACM DL) BibTeX
- Fusun Yaman, Thomas J. Walsh, Michael L. Littman, Marie desJardins:
Democratic approximation of lexicographic preference models.
1200-1207
Electronic Edition (ACM DL) BibTeX
- Hengshuai Yao, Zhi-Qiang Liu:
Preconditioned temporal difference learning.
1208-1215
Electronic Edition (ACM DL) BibTeX
- Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph:
A quasi-Newton approach to non-smooth convex optimization.
1216-1223
Electronic Edition (ACM DL) BibTeX
- Yisong Yue, Thorsten Joachims:
Predicting diverse subsets using structural SVMs.
1224-1231
Electronic Edition (ACM DL) BibTeX
- Kai Zhang, Ivor W. Tsang, James T. Kwok:
Improved Nyström low-rank approximation and error analysis.
1232-1239
Electronic Edition (ACM DL) BibTeX
- Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung:
Estimating local optimums in EM algorithm over Gaussian mixture model.
1240-1247
Electronic Edition (ACM DL) BibTeX
- Bin Zhao, Fei Wang, Changshui Zhang:
Efficient multiclass maximum margin clustering.
1248-1255
Electronic Edition (ACM DL) BibTeX
- Jun Zhu, Eric P. Xing, Bo Zhang:
Laplace maximum margin Markov networks.
1256-1263
Electronic Edition (ACM DL) BibTeX
Copyright © Sat May 16 23:20:41 2009
by Michael Ley (ley@uni-trier.de)
