2013
266MLbase: A Distributed Machine-learning System. Tim Kraska, Ameet Talwalkar, John C. Duchi, Rean Griffith, Michael J. Franklin, Michael I. Jordan. CIDR 2013. Web SearchBibTeXDownload
265Learning Dependency-Based Compositional Semantics. Percy Liang, Michael I. Jordan, Dan Klein. Computational Linguistics (39): 389-446 (2013). Web SearchBibTeXDownload
264Variational MCMC. Nando de Freitas, Pedro A. d. F. R. H°jen-S°rensen, Stuart J. Russell, Stuart J. Russell. CoRR (abs/1301.2266) (2013). Web SearchBibTeXDownload
263Loopy Belief Propogation and Gibbs Measures. Sekhar Tatikonda, Michael I. Jordan. CoRR (abs/1301.0605) (2013). Web SearchBibTeXDownload
262Local Privacy and Statistical Minimax Rates. John C. Duchi, Michael I. Jordan, Martin J. Wainwright. CoRR (abs/1302.3203) (2013). Web SearchBibTeXDownload
261Mixture Representations for Inference and Learning in Boltzmann Machines. Neil D. Lawrence, Christopher M. Bishop, Michael I. Jordan. CoRR (abs/1301.7393) (2013). Web SearchBibTeXDownload
260Loopy Belief Propagation for Approximate Inference: An Empirical Study. Kevin P. Murphy, Yair Weiss, Michael I. Jordan. CoRR (abs/1301.6725) (2013). Web SearchBibTeXDownload
259Tree-dependent Component Analysis. Francis R. Bach, Michael I. Jordan. CoRR (abs/1301.0554) (2013). Web SearchBibTeXDownload
258Computing Upper and Lower Bounds on Likelihoods in Intractable Networks. Tommi Jaakkola, Michael I. Jordan. CoRR (abs/1302.3586) (2013). Web SearchBibTeXDownload
257PEGASUS: A Policy Search Method for Large MDPs and POMDPs. Andrew Y. Ng, Michael I. Jordan. CoRR (abs/1301.3878) (2013). Web SearchBibTeXDownload
256Divide-and-Conquer Subspace Segmentation. Ameet Talwalkar, Lester W. Mackey, Yadong Mu, Shih-Fu Chang, Michael I. Jordan. CoRR (abs/1304.5583) (2013). Web SearchBibTeXDownload
255Efficient Stepwise Selection in Decomposable Models. Amol Deshpande, Minos N. Garofalakis, Michael I. Jordan. CoRR (abs/1301.2267) (2013). Cited by 42Web SearchBibTeXDownload
2012
254Computational and Statistical Tradeoffs via Convex Relaxation. Venkat Chandrasekaran, Michael I. Jordan. CoRR (abs/1211.1073) (2012). Web SearchBibTeXDownload
253Graph partition strategies for generalized mean field inference. Eric P. Xing, Michael I. Jordan, Stuart J. Russell. CoRR (abs/1207.4156) (2012). Web SearchBibTeXDownload
252Optimization of Structured Mean Field Objectives. Alexandre Bouchard-C˘tÚ, Michael I. Jordan. CoRR (abs/1205.2658) (2012). Web SearchBibTeXDownload
251The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features. Kurt T. Miller, Thomas L. Griffiths, Michael I. Jordan. CoRR (abs/1206.3279) (2012). Web SearchBibTeXDownload
250Nested Hierarchical Dirichlet Processes. John William Paisley, Chong Wang, David M. Blei, Michael I. Jordan. CoRR (abs/1210.6738) (2012). Web SearchBibTeXDownload
249Active Learning for Crowd-Sourced Databases. Barzan Mozafari, Purnamrita Sarkar, Michael J. Franklin, Michael I. Jordan, Samuel Madden. CoRR (abs/1209.3686) (2012). Web SearchBibTeXDownload
248A Generalized Mean Field Algorithm for Variational Inference in Exponential Families. Eric P. Xing, Michael I. Jordan, Stuart J. Russell. CoRR (abs/1212.2512) (2012). Web SearchBibTeXDownload
247The Asymptotics of Ranking Algorithms. John C. Duchi, Lester W. Mackey, Michael I. Jordan. CoRR (abs/1204.1688) (2012). Web SearchBibTeXDownload
246Modeling Events with Cascades of Poisson Processes. Aleksandr Simma, Michael I. Jordan. CoRR (abs/1203.3516) (2012). Web SearchBibTeXDownload
245Privacy Aware Learning. John C. Duchi, Michael I. Jordan, Martin J. Wainwright. CoRR (abs/1210.2085) (2012). Web SearchBibTeXDownload
244The DLR Hierarchy of Approximate Inference. Michal Rosen-Zvi, Michael I. Jordan, Alan L. Yuille. CoRR (abs/1207.1417) (2012). Web SearchBibTeXDownload
243The Big Data Bootstrap. Ariel Kleiner, Ameet Talwalkar, Purnamrita Sarkar, Michael I. Jordan. ICML 2012. Web SearchBibTeXDownload
242Variational Bayesian Inference with Stochastic Search. John William Paisley, David M. Blei, Michael I. Jordan. ICML 2012. Web SearchBibTeXDownload
241Nonparametric Link Prediction in Dynamic Networks. Purnamrita Sarkar, Deepayan Chakrabarti, Michael I. Jordan. ICML 2012. Web SearchBibTeXDownload
240Revisiting k-means: New Algorithms via Bayesian Nonparametrics. Brian Kulis, Michael I. Jordan. ICML 2012. Web SearchBibTeXDownload
239Qualcomm Context-Awareness Symposium Sets Research Agenda for Context-Aware Smartphones. Paul Lukowicz, Sanjiv Nanda, Vidya Narayanan, Hal Albelson, Deborah L. McGuinness, Michael I. Jordan. IEEE Pervasive Computing (11): 76-79 (2012). Web SearchBibTeXDownload
238Stick-Breaking Beta Processes and the Poisson Process. John William Paisley, David M. Blei, Michael I. Jordan. Journal of Machine Learning Research - Proceedings Track (22): 850-858 (2012). Web SearchBibTeXDownload
237Active spectral clustering via iterative uncertainty reduction. Fabian L. Wauthier, Nebojsa Jojic, Michael I. Jordan. KDD 2012, 1339-1347. Web SearchBibTeXDownload
236Divide-and-conquer and statistical inference for big data. Michael I. Jordan. KDD 2012, 4. Web SearchBibTeXDownload
235Ancestor Sampling for Particle Gibbs. Fredrik Lindsten, Michael I. Jordan, Thomas B. Sch÷n. NIPS 2012, 2600-2608. Web SearchBibTeXDownload
234Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods. John C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono. NIPS 2012, 1448-1456. Web SearchBibTeXDownload
233Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models. Ke Jiang, Brian Kulis, Michael I. Jordan. NIPS 2012, 3167-3175. Web SearchBibTeXDownload
232Ergodic Mirror Descent. John C. Duchi, Alekh Agarwal, Mikael Johansson, Michael I. Jordan. SIAM Journal on Optimization (22): 1549-1578 (2012). Web SearchBibTeXDownload
2011
231Learning Dependency-Based Compositional Semantics. Percy Liang, Michael I. Jordan, Dan Klein. ACL 2011, 590-599. Web SearchBibTeXDownload
230Visually Relating Gene Expression and in vivo DNA Binding Data. Min-Yu Huang, Lester W. Mackey, Soile V. E. Kerńnen, Gunther H. Weber, Michael I. Jordan, David W. Knowles, Mark D. Biggin, Bernd Hamann. BIBM 2011, 586-589. Web SearchBibTeXDownload
229Cluster Forests. Donghui Yan, Aiyou Chen, Michael I. Jordan. CoRR (abs/1104.2930) (2011). Web SearchBibTeXDownload
228Revisiting k-means: New Algorithms via Bayesian Nonparametrics. Brian Kulis, Michael I. Jordan. CoRR (abs/1111.0352) (2011). Web SearchBibTeXDownload
227Variational Probabilistic Inference and the QMR-DT Network. Tommi Jaakkola, Michael I. Jordan. CoRR (abs/1105.5462) (2011). Web SearchBibTeXDownload
226Divide-and-Conquer Matrix Factorization. Lester W. Mackey, Ameet Talwalkar, Michael I. Jordan. CoRR (abs/1107.0789) (2011). Web SearchBibTeXDownload
225Non-parametric Link Prediction. Purnamrita Sarkar, Deepayan Chakrabarti, Michael I. Jordan. CoRR (abs/1109.1077) (2011). Web SearchBibTeXDownload
224Supervised hierarchical Pitman-Yor process for natural scene segmentation. Alex Shyr, Trevor Darrell, Michael I. Jordan, Raquel Urtasun. CVPR 2011, 2281-2288. Web SearchBibTeXDownload
223The SCADS Director: Scaling a Distributed Storage System Under Stringent Performance Requirements. Beth Trushkowsky, Peter BodÝk, Armando Fox, Michael J. Franklin, Michael I. Jordan, David A. Patterson. FAST 2011, 163-176. Web SearchBibTeXDownload
222A Unified Probabilistic Model for Global and Local Unsupervised Feature Selection. Yue Guan, Jennifer G. Dy, Michael I. Jordan. ICML 2011, 1073-1080. Web SearchBibTeX
221Learning Low-Dimensional Signal Models. Lawrence Carin, Richard G. Baraniuk, Volkan Cevher, David B. Dunson, Michael I. Jordan, Guillermo Sapiro, Michael B. Wakin. IEEE Signal Process. Mag. (28): 39-51 (2011). Web SearchBibTeXDownload
220Bayesian Nonparametric Inference of Switching Dynamic Linear Models. Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky. IEEE Transactions on Signal Processing (59): 1569-1585 (2011). Web SearchBibTeXDownload
219Bayesian Generalized Kernel Mixed Models. Zhihua Zhang, Guang Dai, Michael I. Jordan. Journal of Machine Learning Research (12): 111-139 (2011). Web SearchBibTeXDownload
218Dimensionality Reduction for Spectral Clustering. Donglin Niu, Jennifer G. Dy, Michael I. Jordan. Journal of Machine Learning Research - Proceedings Track (15): 552-560 (2011). Web SearchBibTeXDownload
217Bayesian Bias Mitigation for Crowdsourcing. Fabian L. Wauthier, Michael I. Jordan. NIPS 2011, 1800-1808. Web SearchBibTeXDownload
216Nonparametric Combinatorial Sequence Models. Fabian L. Wauthier, Michael I. Jordan, Nebojsa Jojic. RECOMB 2011, 516-530. Web SearchBibTeXDownload
215Managing data transfers in computer clusters with orchestra. Mosharaf Chowdhury, Matei Zaharia, Justin Ma, Michael I. Jordan, Ion Stoica. SIGCOMM 2011, 98-109. Web SearchBibTeXDownload
2010
214Active site prediction using evolutionary and structural information. Sriram Sankararaman, Fei Sha, Jack F. Kirsch, Michael I. Jordan, Kimmen Sj÷lander. Bioinformatics (26): 617-624 (2010). Web SearchBibTeXDownload
213Bayesian Inference in Queueing Networks. Charles A. Sutton, Michael I. Jordan. CoRR (abs/1001.3355) (2010). Web SearchBibTeXDownload
212Sufficient dimension reduction for visual sequence classification. Alex Shyr, Raquel Urtasun, Michael I. Jordan. CVPR 2010, 3610-3617. Web SearchBibTeXDownload
211Type-Based MCMC. Percy Liang, Michael I. Jordan, Dan Klein. HLT-NAACL 2010, 573-581. Web SearchBibTeXDownload
210Multiple Non-Redundant Spectral Clustering Views. Donglin Niu, Jennifer G. Dy, Michael I. Jordan. ICML 2010, 831-838. Web SearchBibTeXDownload
209Mixed Membership Matrix Factorization. Lester W. Mackey, David Weiss, Michael I. Jordan. ICML 2010, 711-718. Web SearchBibTeXDownload
208An Analysis of the Convergence of Graph Laplacians. Daniel Ting, Ling Huang, Michael I. Jordan. ICML 2010, 1079-1086. Web SearchBibTeXDownload
207Learning Programs: A Hierarchical Bayesian Approach. Percy Liang, Michael I. Jordan, Dan Klein. ICML 2010, 639-646. Web SearchBibTeXDownload
206On the Consistency of Ranking Algorithms. John Duchi, Lester W. Mackey, Michael I. Jordan. ICML 2010, 327-334. Web SearchBibTeXDownload
205Detecting Large-Scale System Problems by Mining Console Logs. Wei Xu, Ling Huang, Armando Fox, David Patterson, Michael I. Jordan. ICML 2010, 37-46. Web SearchBibTeXDownload
204Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. IEEE Transactions on Information Theory (56): 5847-5861 (2010). Web SearchBibTeXDownload
203Convex and Semi-Nonnegative Matrix Factorizations. Chris H. Q. Ding, Tao Li, Michael I. Jordan. IEEE Trans. Pattern Anal. Mach. Intell. (32): 45-55 (2010). Web SearchBibTeXDownload
202The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies. David M. Blei, Thomas L. Griffiths, Michael I. Jordan. J. ACM (57) (2010). Web SearchBibTeXDownload
201Regularized Discriminant Analysis, Ridge Regression and Beyond. Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jordan. Journal of Machine Learning Research (11): 2199-2228 (2010). Web SearchBibTeXDownload
200Bayesian Generalized Kernel Models. Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. Jordan. Journal of Machine Learning Research - Proceedings Track (9): 972-979 (2010). Web SearchBibTeXDownload
199Inference and Learning in Networks of Queues. Charles A. Sutton, Michael I. Jordan. Journal of Machine Learning Research - Proceedings Track (9): 796-803 (2010). Web SearchBibTeXDownload
198Matrix-Variate Dirichlet Process Mixture Models. Zhihua Zhang, Guang Dai, Michael I. Jordan. Journal of Machine Learning Research - Proceedings Track (9): 980-987 (2010). Web SearchBibTeXDownload
197Random Conic Pursuit for Semidefinite Programming. Ariel Kleiner, Ali Rahimi, Michael I. Jordan. NIPS 2010, 1135-1143. Web SearchBibTeXDownload
196Variational Inference over Combinatorial Spaces. Alexandre Bouchard-C˘tÚ, Michael I. Jordan. NIPS 2010, 280-288. Web SearchBibTeXDownload
195Unsupervised Kernel Dimension Reduction. Meihong Wang, Fei Sha, Michael I. Jordan. NIPS 2010, 2379-2387. Web SearchBibTeXDownload
194Heavy-Tailed Process Priors for Selective Shrinkage. Fabian L. Wauthier, Michael I. Jordan. NIPS 2010, 2406-2414. Web SearchBibTeXDownload
193Tree-Structured Stick Breaking for Hierarchical Data. Ryan Prescott Adams, Zoubin Ghahramani, Michael I. Jordan. NIPS 2010, 19-27. Web SearchBibTeXDownload
192Neighbor-Dependent Ramachandran Probability Distributions of Amino Acids Developed from a Hierarchical Dirichlet Process Model. Daniel Ting, Guoli Wang, Maxim V. Shapovalov, Rajib Mitra, Michael I. Jordan, Roland L. Dunbrack Jr.. PLoS Computational Biology (6) (2010). Web SearchBibTeXDownload
191Characterizing, modeling, and generating workload spikes for stateful services. Peter BodÝk, Armando Fox, Michael J. Franklin, Michael I. Jordan, David A. Patterson. SoCC 2010, 241-252. Web SearchBibTeXDownload
190Joint covariate selection and joint subspace selection for multiple classification problems. Guillaume Obozinski, Ben Taskar, Michael I. Jordan. Statistics and Computing (20): 231-252 (2010). Web SearchBibTeXDownload
189Modeling Events with Cascades of Poisson Processes. Aleksandr Simma, Michael I. Jordan. UAI 2010, 546-555. Web SearchBibTeXDownload
2009
188Learning Semantic Correspondences with Less Supervision. Percy Liang, Michael I. Jordan, Dan Klein. ACL/IJCNLP 2009, 91-99. Web SearchBibTeXDownload
187Joint estimation of gene conversion rates and mean conversion tract lengths from population SNP data. Junming Yin, Michael I. Jordan, Yun S. Song. Bioinformatics (25) (2009). Web SearchBibTeXDownload
186A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis. Zhihua Zhang, Guang Dai, Michael I. Jordan. ECML/PKDD (2) 2009, 632-647. Web SearchBibTeXDownload
185Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning. Archana Ganapathi, Harumi A. Kuno, Umeshwar Dayal, Janet L. Wiener, Armando Fox, Michael I. Jordan, David A. Patterson. ICDE 2009, 592-603. Cited by 9Web SearchBibTeXDownload
184Online System Problem Detection by Mining Patterns of Console Logs. Wei Xu, Ling Huang, Armando Fox, David Patterson, Michael I. Jordan. ICDM 2009, 588-597. Web SearchBibTeXDownload
183Learning from measurements in exponential families. Percy Liang, Michael I. Jordan, Dan Klein. ICML 2009, 81. Web SearchBibTeXDownload
182Latent Variable Models for Dimensionality Reduction. Zhihua Zhang, Michael I. Jordan. Journal of Machine Learning Research - Proceedings Track (5): 655-662 (2009). Web SearchBibTeXDownload
181Coherence Functions for Multicategory Margin-based Classification Methods. Zhihua Zhang, Michael I. Jordan, Wu-Jun Li, Dit-Yan Yeung. Journal of Machine Learning Research - Proceedings Track (5): 647-654 (2009). Web SearchBibTeXDownload
180Fast approximate spectral clustering. Donghui Yan, Ling Huang, Michael I. Jordan. KDD 2009, 907-916. Web SearchBibTeXDownload
179Nonparametric Latent Feature Models for Link Prediction. Kurt T. Miller, Thomas L. Griffiths, Michael I. Jordan. NIPS 2009, 1276-1284. Web SearchBibTeXDownload
178Asymptotically Optimal Regularization in Smooth Parametric Models. Percy Liang, Francis R. Bach, Guillaume Bouchard, Michael I. Jordan. NIPS 2009, 1132-1140. Web SearchBibTeXDownload
177Sharing Features among Dynamical Systems with Beta Processes. Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky. NIPS 2009, 549-557. Web SearchBibTeXDownload
176Combinatorial stochastic processes and nonparametric Bayesian modeling. Michael I. Jordan. SODA 2009, 139. Web SearchBibTeXDownload
175Detecting large-scale system problems by mining console logs. Wei Xu, Ling Huang, Armando Fox, David A. Patterson, Michael I. Jordan. SOSP 2009, 117-132. Web SearchBibTeXDownload
174Optimization of Structured Mean Field Objectives. Alexandre Bouchard-C˘tÚ, Michael I. Jordan. UAI 2009, 67-74. Web SearchBibTeXDownload
2008
173Estimating divergence functionals and the likelihood ratio by convex risk minimization. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. CoRR (abs/0809.0853) (2008). Web SearchBibTeXDownload
172Graphical Models, Exponential Families, and Variational Inference. Martin J. Wainwright, Michael I. Jordan. Foundations and Trends in Machine Learning (1): 1-305 (2008). Web SearchBibTeXDownload
171Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding. Chris H. Q. Ding, Tao Li, Michael I. Jordan. ICDM 2008, 183-192. Web SearchBibTeXDownload
170An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators. Percy Liang, Michael I. Jordan. ICML 2008, 584-591. Web SearchBibTeXDownload
169An HDP-HMM for systems with state persistence. Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky. ICML 2008, 312-319. Web SearchBibTeXDownload
168On Optimal Quantization Rules for Some Problems in Sequential Decentralized Detection. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. IEEE Transactions on Information Theory (54): 3285-3295 (2008). Web SearchBibTeXDownload
167Nonparametric Bayesian Learning of Switching Linear Dynamical Systems. Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky. NIPS 2008, 457-464. Web SearchBibTeXDownload
166Spectral Clustering with Perturbed Data. Ling Huang, Donghui Yan, Michael I. Jordan, Nina Taft. NIPS 2008, 705-712. Web SearchBibTeXDownload
165Efficient Inference in Phylogenetic InDel Trees. Alexandre Bouchard-C˘tÚ, Michael I. Jordan, Dan Klein. NIPS 2008, 177-184. Web SearchBibTeXDownload
164High-dimensional support union recovery in multivariate regression. Guillaume Obozinski, Martin J. Wainwright, Michael I. Jordan. NIPS 2008, 1217-1224. Web SearchBibTeXDownload
163Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes. Erik B. Sudderth, Michael I. Jordan. NIPS 2008, 1585-1592. Web SearchBibTeXDownload
162Posterior Consistency of the Silverman g-prior in Bayesian Model Choice. Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung. NIPS 2008, 1969-1976. Web SearchBibTeXDownload
161DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification. Simon Lacoste-Julien, Fei Sha, Michael I. Jordan. NIPS 2008, 897-904. Web SearchBibTeXDownload
160A Dual Receptor Crosstalk Model of G-Protein-Coupled Signal Transduction. Patrick Flaherty, Mala L. Radhakrishnan, Tuan Dinh, Robert A. Rebres, Tamara I. Roach, Michael I. Jordan, Adam P. Arkin. PLoS Computational Biology (4) (2008). Web SearchBibTeXDownload
159On the Inference of Ancestries in Admixed Populations. Sriram Sankararaman, Gad Kimmel, Eran Halperin, Michael I. Jordan. RECOMB 2008, 424-433. Web SearchBibTeXDownload
158Probabilistic Inference in Queueing Networks. Charles A. Sutton, Michael I. Jordan. SysML 2008. Web SearchBibTeXDownload
157Mining Console Logs for Large-Scale System Problem Detection. Wei Xu, Ling Huang, Armando Fox, David A. Patterson, Michael I. Jordan. SysML 2008. Web SearchBibTeXDownload
156The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features. Kurt T. Miller, Thomas L. Griffiths, Michael I. Jordan. UAI 2008, 403-410. Web SearchBibTeXDownload
2007
155Statistical Machine Learning and Computational Biology. Michael I. Jordan. BIBM 2007, 4. Web SearchBibTeXDownload
154The Infinite PCFG Using Hierarchical Dirichlet Processes. Percy Liang, Slav Petrov, Michael I. Jordan, Dan Klein. EMNLP-CoNLL 2007, 688-697. Web SearchBibTeXDownload
153Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes. Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jordan. ICCV 2007, 1-8. Web SearchBibTeXDownload
152Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization. Tao Li, Chris H. Q. Ding, Michael I. Jordan. ICDM 2007, 577-582. Web SearchBibTeXDownload
151Image Denoising with Nonparametric Hidden Markov Trees. Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jordan. ICIP (3) 2007, 121-124. Web SearchBibTeXDownload
150Regression on manifolds using kernel dimension reduction. Jens Nilsson, Fei Sha, Michael I. Jordan. ICML 2007, 697-704. Web SearchBibTeXDownload
149A permutation-augmented sampler for DP mixture models. Percy Liang, Michael I. Jordan, Benjamin Taskar. ICML 2007, 545-552. Web SearchBibTeXDownload
148Communication-Efficient Online Detection of Network-Wide Anomalies. Ling Huang, XuanLong Nguyen, Minos N. Garofalakis, Joseph M. Hellerstein, Michael I. Jordan, Anthony D. Joseph, Nina Taft. INFOCOM 2007, 134-142. Cited by 26Web SearchBibTeXDownload
147Bayesian Haplotype Inference via the Dirichlet Process. Eric P. Xing, Michael I. Jordan, Roded Sharan. Journal of Computational Biology (14): 267-284 (2007). Web SearchBibTeXDownload
146Hierarchical Beta Processes and the Indian Buffet Process. Romain Thibaux, Michael I. Jordan. Journal of Machine Learning Research - Proceedings Track (2): 564-571 (2007). Web SearchBibTeXDownload
145Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. NIPS 2007. Web SearchBibTeXDownload
144Agreement-Based Learning. Percy Liang, Dan Klein, Michael I. Jordan. NIPS 2007. Web SearchBibTeXDownload
143Feature Selection Methods for Improving Protein Structure Prediction with Rosetta. Ben Blum, Michael I. Jordan, David Kim, Rhiju Das, Philip Bradley, David Baker. NIPS 2007. Web SearchBibTeXDownload
2006
142Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span. David M. Blei, K. Franks, Michael I. Jordan, I. Saira Mian. BMC Bioinformatics (7): 250 (2006). Web SearchBibTeXDownload
141On optimal quantization rules for some sequential decision problems. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. CoRR (abs/math/0608556) (2006). Web SearchBibTeXDownload
140Word Alignment via Quadratic Assignment. Simon Lacoste-Julien, Benjamin Taskar, Dan Klein, Michael I. Jordan. HLT-NAACL 2006. Web SearchBibTeXDownload
139Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture. Eric P. Xing, Kyung-Ah Sohn, Michael I. Jordan, Yee Whye Teh. ICML 2006, 1049-1056. Web SearchBibTeXDownload
138Statistical debugging: simultaneous identification of multiple bugs. Alice X. Zheng, Michael I. Jordan, Ben Liblit, Mayur Naik, Alex Aiken. ICML 2006, 1105-1112. Web SearchBibTeXDownload
137A graphical model for predicting protein molecular function. Barbara E. Engelhardt, Michael I. Jordan, Steven E. Brenner. ICML 2006, 297-304. Web SearchBibTeXDownload
136Log-determinant relaxation for approximate inference in discrete Markov random fields. Martin J. Wainwright, Michael I. Jordan. IEEE Transactions on Signal Processing (54): 2099-2109 (2006). Web SearchBibTeXDownload
135Structured Prediction, Dual Extragradient and Bregman Projections. Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan. Journal of Machine Learning Research (7): 1627-1653 (2006). Web SearchBibTeXDownload
134Learning Spectral Clustering, With Application To Speech Separation. Francis R. Bach, Michael I. Jordan. Journal of Machine Learning Research (7): 1963-2001 (2006). Web SearchBibTeXDownload
133In-Network PCA and Anomaly Detection. Ling Huang, XuanLong Nguyen, Minos N. Garofalakis, Michael I. Jordan, Anthony D. Joseph, Nina Taft. NIPS 2006, 617-624. Cited by 19Web SearchBibTeXDownload
132Nonparametric empirical Bayes for the Dirichlet process mixture model. Jon D. McAuliffe, David M. Blei, Michael I. Jordan. Statistics and Computing (16): 5-14 (2006). Web SearchBibTeXDownload
131Bayesian Multicategory Support Vector Machines. Zhihua Zhang, Michael I. Jordan. UAI 2006. Web SearchBibTeXDownload
2005
130A latent variable model for chemogenomic profiling. Patrick Flaherty, Guri Giaever, Jochen Kumm, Michael I. Jordan, Adam P. Arkin. Bioinformatics (21): 3286-3293 (2005). Web SearchBibTeXDownload
129On divergences, surrogate loss functions, and decentralized detection. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. CoRR (abs/math/0510521) (2005). Web SearchBibTeXDownload
128Combining Visualization and Statistical Analysis to Improve Operator Confidence and Efficiency for Failure Detection and Localization. Peter BodÝk, Greg Friedman, Lukas Biewald, Helen Levine, George Candea, Kayur Patel, Gilman Tolle, Jonathan Hui, Armando Fox, Michael I. Jordan, David A. Patterson. ICAC 2005, 89-100. Web SearchBibTeXDownload
127Predictive low-rank decomposition for kernel methods. Francis R. Bach, Michael I. Jordan. ICML 2005, 33-40. Web SearchBibTeXDownload
126Divergences, surrogate loss functions and experimental design. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. NIPS 2005. Web SearchBibTeXDownload
125Structured Prediction via the Extragradient Method. Benjamin Taskar, Simon Lacoste-Julien, Michael I. Jordan. NIPS 2005. Web SearchBibTeXDownload
124Robust design of biological experiments. Patrick Flaherty, Michael I. Jordan, Adam P. Arkin. NIPS 2005. Web SearchBibTeXDownload
123Scalable statistical bug isolation. Ben Liblit, Mayur Naik, Alice X. Zheng, Alexander Aiken, Michael I. Jordan. PLDI 2005, 15-26. Web SearchBibTeXDownload
122Protein Molecular Function Prediction by Bayesian Phylogenomics. Barbara E. Engelhardt, Michael I. Jordan, Kathryn E. Muratore, Steven E. Brenner. PLoS Computational Biology (1) (2005). Web SearchBibTeXDownload
121A kernel-based learning approach to ad hoc sensor network localization. XuanLong Nguyen, Michael I. Jordan, Bruno Sinopoli. TOSN (1): 134-152 (2005). Web SearchBibTeXDownload
120The DLR Hierarchy of Approximate Inference. Michal Rosen-Zvi, Michael I. Jordan, Alan L. Yuille. UAI 2005, 493-500. Web SearchBibTeXDownload
2004
119A statistical framework for genomic data fusion. Gert R. G. Lanckriet, Tijl De Bie, Nello Cristianini, Michael I. Jordan, William Stafford Noble. Bioinformatics (20): 2626-2635 (2004). Web SearchBibTeXDownload
118Multiple-sequence functional annotation and the generalized hidden Markov phylogeny. Jon D. McAuliffe, Lior Pachter, Michael I. Jordan. Bioinformatics (20): 1850-1860 (2004). Web SearchBibTeXDownload
117A direct formulation for sparse PCA using semidefinite programming. Alexandre d'Aspremont, Laurent El Ghaoui, Michael I. Jordan, Gert R. G. Lanckriet. CoRR (cs.CE/0406021) (2004). Web SearchBibTeXDownload
116Extensions of the Informative Vector Machine. Neil D. Lawrence, John C. Platt, Michael I. Jordan. Deterministic and Statistical Methods in Machine Learning 2004, 56-87. Web SearchBibTeXDownload
115Failure Diagnosis Using Decision Trees. Mike Y. Chen, Alice X. Zheng, Jim Lloyd, Michael I. Jordan, Eric A. Brewer. ICAC 2004, 36-43. Web SearchBibTeXDownload
114Variational methods for the Dirichlet process. David M. Blei, Michael I. Jordan. ICML 2004. Web SearchBibTeXDownload
113Decentralized detection and classification using kernel methods. XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. ICML 2004. Web SearchBibTeXDownload
112Multiple kernel learning, conic duality, and the SMO algorithm. Francis R. Bach, Gert R. G. Lanckriet, Michael I. Jordan. ICML 2004. Web SearchBibTeXDownload
111Bayesian haplo-type inference via the dirichlet process. Eric P. Xing, Roded Sharan, Michael I. Jordan. ICML 2004. Web SearchBibTeXDownload
110Learning graphical models for stationary time series. Francis R. Bach, Michael I. Jordan. IEEE Transactions on Signal Processing (52): 2189-2199 (2004). Web SearchBibTeXDownload
109Kalman filtering with intermittent observations. Bruno Sinopoli, Luca Schenato, Massimo Franceschetti, Kameshwar Poolla, Michael I. Jordan, Shankar S. Sastry. IEEE Trans. Automat. Contr. (49): 1453-1464 (2004). Web SearchBibTeXDownload
108Logos: a Modular Bayesian Model for de Novo Motif Detection. Eric P. Xing, Wei Wu, Michael I. Jordan, Richard M. Karp. J. Bioinformatics and Computational Biology (2): 127-154 (2004). Web SearchBibTeXDownload
107Robust Sparse Hyperplane Classifiers: Application to Uncertain Molecular Profiling Data. Chiranjib Bhattacharyya, L. R. Grate, Michael I. Jordan, Laurent El Ghaoui, I. Saira Mian. Journal of Computational Biology (11): 1073-1089 (2004). Web SearchBibTeXDownload
106Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces. Kenji Fukumizu, Francis R. Bach, Michael I. Jordan. Journal of Machine Learning Research (5): 73-99 (2004). Web SearchBibTeXDownload
105Learning the Kernel Matrix with Semidefinite Programming. Gert R. G. Lanckriet, Nello Cristianini, Peter L. Bartlett, Laurent El Ghaoui, Michael I. Jordan. Journal of Machine Learning Research (5): 27-72 (2004). Web SearchBibTeXDownload
104Computing regularization paths for learning multiple kernels. Francis R. Bach, Romain Thibaux, Michael I. Jordan. NIPS 2004. Web SearchBibTeXDownload
103Semi-supervised Learning via Gaussian Processes. Neil D. Lawrence, Michael I. Jordan. NIPS 2004. Web SearchBibTeXDownload
102Blind One-microphone Speech Separation: A Spectral Learning Approach. Francis R. Bach, Michael I. Jordan. NIPS 2004. Web SearchBibTeXDownload
101A Direct Formulation for Sparse PCA Using Semidefinite Programming. Alexandre d'Aspremont, Laurent El Ghaoui, Michael I. Jordan, Gert R. G. Lanckriet. NIPS 2004. Web SearchBibTeXDownload
100Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes. Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, David M. Blei. NIPS 2004. Web SearchBibTeXDownload
99Kernel-Based Data Fusion and Its Application to Protein Function Prediction in Yeast. Gert R. G. Lanckriet, Minghua Deng, Nello Cristianini, Michael I. Jordan, William Stafford Noble. Pacific Symposium on Biocomputing 2004, 300-311. Web SearchBibTeXDownload
98Graph Partition Strategies for Generalized Mean Field Inference. Eric P. Xing, Michael I. Jordan. UAI 2004, 602-610. Web SearchBibTeXDownload
2003
97LOGOS: a modular Bayesian model for de novo motif detection. Eric P. Xing, Wei Wu, Michael I. Jordan, Richard M. Karp. CSB 2003, 266-276. Web SearchBibTeXDownload
96Support vector machines for analog circuit performance representation. Fernando De Bernardinis, Michael I. Jordan, Alberto L. Sangiovanni-Vincentelli. DAC 2003, 964-969. Web SearchBibTeXDownload
95Beyond Independent Components: Trees and Clusters. Francis R. Bach, Michael I. Jordan. Journal of Machine Learning Research (4): 1205-1233 (2003). Web SearchBibTeXDownload
94Matching Words and Pictures. Kobus Barnard, Pinar Duygulu, David A. Forsyth, Nando de Freitas, David M. Blei, Michael I. Jordan. Journal of Machine Learning Research (3): 1107-1135 (2003). Web SearchBibTeXDownload
93Latent Dirichlet Allocation. David M. Blei, Andrew Y. Ng, Michael I. Jordan. Journal of Machine Learning Research (3): 993-1022 (2003). Web SearchBibTeXDownload
92An Introduction to MCMC for Machine Learning. Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan. Machine Learning (50): 5-43 (2003). Web SearchBibTeXDownload
91Kernel Dimensionality Reduction for Supervised Learning. Kenji Fukumizu, Francis R. Bach, Michael I. Jordan. NIPS 2003. Web SearchBibTeXDownload
90Statistical Debugging of Sampled Programs. Alice X. Zheng, Michael I. Jordan, Ben Liblit, Alexander Aiken. NIPS 2003. Web SearchBibTeXDownload
89Learning Spectral Clustering. Francis R. Bach, Michael I. Jordan. NIPS 2003. Web SearchBibTeXDownload
88Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates. Peter L. Bartlett, Michael I. Jordan, Jon D. McAuliffe. NIPS 2003. Web SearchBibTeXDownload
87Semidefinite Relaxations for Approximate Inference on Graphs with Cycles. Martin J. Wainwright, Michael I. Jordan. NIPS 2003. Web SearchBibTeXDownload
86Autonomous Helicopter Flight via Reinforcement Learning. Andrew Y. Ng, H. Jin Kim, Michael I. Jordan, Shankar Sastry. NIPS 2003. Web SearchBibTeXDownload
85Hierarchical Topic Models and the Nested Chinese Restaurant Process. David M. Blei, Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum. NIPS 2003. Web SearchBibTeXDownload
84On the Concentration of Expectation and Approximate Inference in Layered Networks. XuanLong Nguyen, Michael I. Jordan. NIPS 2003. Web SearchBibTeXDownload
83Bug isolation via remote program sampling. Ben Liblit, Alexander Aiken, Alice X. Zheng, Michael I. Jordan. PLDI 2003, 141-154. Web SearchBibTeXDownload
82Modeling annotated data. David M. Blei, Michael I. Jordan. SIGIR 2003, 127-134. Web SearchBibTeXDownload
81Simultaneous classification and relevant feature identification in high-dimensional spaces: application to molecular profiling data. Chiranjib Bhattacharyya, L. R. Grate, A. Rizki, D. Radisky, F. J. Molina, Michael I. Jordan, Mina J. Bissell, I. Saira Mian. Signal Processing (83): 729-743 (2003). Web SearchBibTeXDownload
80A generalized mean field algorithm for variational inference in exponential families. Eric P. Xing, Michael I. Jordan, Stuart J. Russell. UAI 2003, 583-591. Web SearchBibTeXDownload
2002
79Learning the Kernel Matrix with Semi-Definite Programming. Gert R. G. Lanckriet, Nello Cristianini, Peter L. Bartlett, Laurent El Ghaoui, Michael I. Jordan. ICML 2002, 323-330. Web SearchBibTeX
78A Robust Minimax Approach to Classification. Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan. Journal of Machine Learning Research (3): 555-582 (2002). Web SearchBibTeXDownload
77Kernel Independent Component Analysis. Francis R. Bach, Michael I. Jordan. Journal of Machine Learning Research (3): 1-48 (2002). Web SearchBibTeXDownload
76Distance Metric Learning with Application to Clustering with Side-Information. Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, Stuart J. Russell. NIPS 2002, 505-512. Web SearchBibTeXDownload
75A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences. Eric P. Xing, Michael I. Jordan, Richard M. Karp, Stuart J. Russell. NIPS 2002, 1489-1496. Web SearchBibTeXDownload
74Robust Novelty Detection with Single-Class MPM. Gert R. G. Lanckriet, Laurent El Ghaoui, Michael I. Jordan. NIPS 2002, 905-912. Web SearchBibTeXDownload
73A Minimal Intervention Principle for Coordinated Movement. Emanuel Todorov, Michael I. Jordan. NIPS 2002, 27-34. Web SearchBibTeXDownload
72Learning Graphical Models with Mercer Kernels. Francis R. Bach, Michael I. Jordan. NIPS 2002, 1009-1016. Web SearchBibTeXDownload
71Graphical Models: Foundations of Neural Computation. Michael I. Jordan, Terrence J. Sejnowski. Pattern Anal. Appl. (5): 401-402 (2002). Web SearchBibTeXDownload
70Loopy Belief Propogation and Gibbs Measures. Sekhar Tatikonda, Michael I. Jordan. UAI 2002, 493-500. Web SearchBibTeXDownload
69Tree-dependent Component Analysis. Francis R. Bach, Michael I. Jordan. UAI 2002, 36-44. Web SearchBibTeXDownload
68Simultaneous Relevant Feature Identification and Classification in High-Dimensional Spaces. L. R. Grate, Chiranjib Bhattacharyya, Michael I. Jordan, I. Saira Mian. WABI 2002, 1-9. Web SearchBibTeXDownload
2001
67Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection. Andrew Y. Ng, Michael I. Jordan. ICML 2001, 377-384. Web SearchBibTeX
66Feature selection for high-dimensional genomic microarray data. Eric P. Xing, Michael I. Jordan, Richard M. Karp. ICML 2001, 601-608. Web SearchBibTeX
65Link Analysis, Eigenvectors and Stability. Andrew Y. Ng, Alice X. Zheng, Michael I. Jordan. IJCAI 2001, 903-910. Web SearchBibTeX
64Asymptotic Convergence Rate of the EM Algorithm for Gaussian Mixtures. Jinwen Ma, Lei Xu, Michael I. Jordan. Neural Computation (12): 2881-2907 (2001). Web SearchBibTeXDownload
63On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes. Andrew Y. Ng, Michael I. Jordan. NIPS 2001, 841-848. Web SearchBibTeXDownload
62Latent Dirichlet Allocation. David M. Blei, Andrew Y. Ng, Michael I. Jordan. NIPS 2001, 601-608. Web SearchBibTeXDownload
61On Spectral Clustering: Analysis and an algorithm. Andrew Y. Ng, Michael I. Jordan, Yair Weiss. NIPS 2001, 849-856. Web SearchBibTeXDownload
60Thin Junction Trees. Francis R. Bach, Michael I. Jordan. NIPS 2001, 569-576. Web SearchBibTeXDownload
59Minimax Probability Machine. Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan. NIPS 2001, 801-807. Web SearchBibTeXDownload
58Stable Algorithms for Link Analysis. Alice X. Zheng, Andrew Y. Ng, Michael I. Jordan. SIGIR 2001, 258-266. Web SearchBibTeXDownload
57Efficient Stepwise Selection in Decomposable Models. Amol Deshpande, Minos N. Garofalakis, Michael I. Jordan. UAI 2001, 128-135. Cited by 42Web SearchBibTeXDownload
2000
56Learning with Mixtures of Trees. Marina Meila, Michael I. Jordan. Journal of Machine Learning Research (1): 1-48 (2000). Web SearchBibTeXDownload
55Attractor Dynamics in Feedforward Neural Networks. Lawrence K. Saul, Michael I. Jordan. Neural Computation (12): 1313-1335 (2000). Web SearchBibTeXDownload
54PEGASUS: A policy search method for large MDPs and POMDPs. Andrew Y. Ng, Michael I. Jordan. UAI 2000, 406-415. Web SearchBibTeXDownload
1999
53Variational Probabilistic Inference and the QMR-DT Network. Tommi Jaakkola, Michael I. Jordan. J. Artif. Intell. Res. (JAIR) (10): 291-322 (1999). Web SearchBibTeXDownload
52An Introduction to Variational Methods for Graphical Models. Michael I. Jordan, Zoubin Ghahramani, Tommi Jaakkola, Lawrence K. Saul. Machine Learning (37): 183-233 (1999). Web SearchBibTeXDownload
51Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones. Lawrence K. Saul, Michael I. Jordan. Machine Learning (37): 75-87 (1999). Web SearchBibTeXDownload
50Approximate Inference A lgorithms for Two-Layer Bayesian Networks. Andrew Y. Ng, Michael I. Jordan. NIPS 1999, 533-539. Web SearchBibTeXDownload
49Loopy Belief Propagation for Approximate Inference: An Empirical Study. Kevin P. Murphy, Yair Weiss, Michael I. Jordan. UAI 1999, 467-475. Web SearchBibTeXDownload
1998
48Learning from Dyadic Data. Thomas Hofmann, Jan Puzicha, Michael I. Jordan. NIPS 1998, 466-472. Web SearchBibTeXDownload
47Mixture Representations for Inference and Learning in Boltzmann Machines. Neil D. Lawrence, Christopher M. Bishop, Michael I. Jordan. UAI 1998, 320-327. Web SearchBibTeXDownload
1997
46Factorial Hidden Markov Models. Zoubin Ghahramani, Michael I. Jordan. Machine Learning (29): 245-273 (1997). Web SearchBibTeXDownload
45Probabilistic Independence Networks for Hidden Markov Probability Models. Padhraic Smyth, David Heckerman, Michael I. Jordan. Neural Computation (9): 227-269 (1997). Web SearchBibTeXDownload
44Adaptation in Speech Motor Control. John F. Houde, Michael I. Jordan. NIPS 1997. Web SearchBibTeX
43Estimating Dependency Structure as a Hidden Variable. Marina Meila, Michael I. Jordan. NIPS 1997. Web SearchBibTeX
42Approximating Posterior Distributions in Belief Networks Using Mixtures. Christopher M. Bishop, Neil D. Lawrence, Tommi Jaakkola, Michael I. Jordan. NIPS 1997. Web SearchBibTeX
41Neural Networks. Michael I. Jordan, Christopher M. Bishop. The Computer Science and Engineering Handbook 1997, 536-556. Web SearchBibTeX
1996
40Neural Networks. Michael I. Jordan, Christopher M. Bishop. ACM Comput. Surv. (28): 73-75 (1996). Web SearchBibTeXDownload
39Active Learning with Statistical Models. David A. Cohn, Zoubin Ghahramani, Michael I. Jordan. CoRR (cs.AI/9603104): 129-145 (1996). Web SearchBibTeXDownload
38Mean Field Theory for Sigmoid Belief Networks. Lawrence K. Saul, Tommi Jaakkola, Michael I. Jordan. CoRR (cs.AI/9603102): 61-76 (1996). Web SearchBibTeXDownload
37Local linear perceptrons for classification. Ethem Alpaydin, Michael I. Jordan. IEEE Trans. Neural Netw. Learning Syst. (7): 788-794 (1996). Web SearchBibTeXDownload
36Triangulation by Continuous Embedding. Marina Meila, Michael I. Jordan. NIPS 1996, 557-563. Web SearchBibTeXDownload
35A Variational Principle for Model-based Morphing. Lawrence K. Saul, Michael I. Jordan. NIPS 1996, 267-273. Web SearchBibTeXDownload
34Hidden Markov Decision Trees. Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul. NIPS 1996, 501-507. Web SearchBibTeXDownload
33Recursive Algorithms for Approximating Probabilities in Graphical Models. Tommi Jaakkola, Michael I. Jordan. NIPS 1996, 487-493. Web SearchBibTeXDownload
32Computing upper and lower bounds on likelihoods in intractable networks. Tommi Jaakkola, Michael I. Jordan. UAI 1996, 340-348. Web SearchBibTeXDownload
1995
31Convergence results for the EM approach to mixtures of experts architectures. Michael I. Jordan, Lei Xu. Neural Networks (8): 1409-1431 (1995). Web SearchBibTeXDownload
30Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks. Tommi Jaakkola, Lawrence K. Saul, Michael I. Jordan. NIPS 1995, 528-534. Web SearchBibTeXDownload
29Reinforcement Learning by Probability Matching. Philip N. Sabes, Michael I. Jordan. NIPS 1995, 1080-1086. Web SearchBibTeXDownload
28Factorial Hidden Markov Models. Zoubin Ghahramani, Michael I. Jordan. NIPS 1995, 472-478. Web SearchBibTeXDownload
27Learning Fine Motion by Markov Mixtures of Experts. Marina Meila, Michael I. Jordan. NIPS 1995, 1003-1009. Web SearchBibTeXDownload
26Exploiting Tractable Substructures in Intractable Networks. Lawrence K. Saul, Michael I. Jordan. NIPS 1995, 486-492. Web SearchBibTeXDownload
1994
25A Statistical Approach to Decision Tree Modeling. Michael I. Jordan. COLT 1994, 13-20. Web SearchBibTeXDownload
24Learning Without State-Estimation in Partially Observable Markovian Decision Processes. Satinder P. Singh, Tommi Jaakkola, Michael I. Jordan. ICML 1994, 284-292. Web SearchBibTeX
23Learning in Boltzmann Trees. Lawrence K. Saul, Michael I. Jordan. Neural Computation (6): 1174-1184 (1994). Web SearchBibTeXDownload
22Hierarchical Mixtures of Experts and the EM Algorithm. Michael I. Jordan, Robert A. Jacobs. Neural Computation (6): 181-214 (1994). Web SearchBibTeXDownload
21On the Convergence of Stochastic Iterative Dynamic Programming Algorithms. Tommi Jaakkola, Michael I. Jordan, Satinder P. Singh. Neural Computation (6): 1185-1201 (1994). Web SearchBibTeXDownload
20Boltzmann Chains and Hidden Markov Models. Lawrence K. Saul, Michael I. Jordan. NIPS 1994, 435-442. Web SearchBibTeXDownload
19Reinforcement Learning with Soft State Aggregation. Satinder P. Singh, Tommi Jaakkola, Michael I. Jordan. NIPS 1994, 361-368. Web SearchBibTeXDownload
18Active Learning with Statistical Models. David A. Cohn, Zoubin Ghahramani, Michael I. Jordan. NIPS 1994, 705-712. Web SearchBibTeXDownload
17An Alternative Model for Mixtures of Experts. Lei Xu, Michael I. Jordan, Geoffrey E. Hinton. NIPS 1994, 633-640. Web SearchBibTeXDownload
16Computational Structure of coordinate transformations: A generalization study. Zoubin Ghahramani, Daniel M. Wolpert, Michael I. Jordan. NIPS 1994, 1125-1132. Web SearchBibTeXDownload
15Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems. Tommi Jaakkola, Satinder P. Singh, Michael I. Jordan. NIPS 1994, 345-352. Web SearchBibTeXDownload
14Forward dynamic models in human motor control: Psychophysical evidence. Daniel M. Wolpert, Zoubin Ghahramani, Michael I. Jordan. NIPS 1994, 43-50. Web SearchBibTeXDownload
1993
13Supervised Learning and Divide-and-Conquer: A Statistical Approach. Michael I. Jordan, Robert A. Jacobs. ICML 1993, 159-166. Web SearchBibTeX
12Learning piecewise control strategies in a modular neural network architecture. Robert A. Jacobs, Michael I. Jordan. IEEE Transactions on Systems, Man, and Cybernetics (23): 337-345 (1993). Web SearchBibTeXDownload
11Task Decompostiion Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto. Machine Learning: From Theory to Applications 1993, 175-202. Web SearchBibTeXDownload
10Supervised learning from incomplete data via an EM approach. Zoubin Ghahramani, Michael I. Jordan. NIPS 1993, 120-127. Web SearchBibTeXDownload
9Convergence of Stochastic Iterative Dynamic Programming Algorithms. Tommi Jaakkola, Michael I. Jordan, Satinder P. Singh. NIPS 1993, 703-710. Web SearchBibTeXDownload
1992
8Forward Models: Supervised Learning with a Distal Teacher. Michael I. Jordan, David E. Rumelhart. Cognitive Science (16): 307-354 (1992). Web SearchBibTeXDownload
7A Dynamical Model of Priming and Repetition Blindness. Daphne Bavelier, Michael I. Jordan. NIPS 1992, 879-886. Web SearchBibTeXDownload
1991
6Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks. Robert A. Jacobs, Michael I. Jordan, Andrew G. Barto. Cognitive Science (15): 219-250 (1991). Web SearchBibTeXDownload
5Internal World Models and Supervised Learning. Michael I. Jordan, David E. Rumelhart. ML 1991, 70-74. Web SearchBibTeX
4Hierarchies of Adaptive Experts. Michael I. Jordan, Robert A. Jacobs. NIPS 1991, 985-992. Web SearchBibTeXDownload
3Forward Dynamics Modeling of Speech Motor Control Using Physiological Data. Makoto Hirayama, Eric Vatikiotis-Bateson, Mitsuo Kawato, Michael I. Jordan. NIPS 1991, 191-198. Web SearchBibTeXDownload
1990
2A Competitive Modular Connectionist Architecture. Robert A. Jacobs, Michael I. Jordan. NIPS 1990, 767-773. Web SearchBibTeXDownload
1989
1Learning to Control an Unstable System with Forward Modeling. Michael I. Jordan, Robert A. Jacobs. NIPS 1989, 324-331. Web SearchBibTeXDownload
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