Michael I. Jordan

Michael I. Jordan is a person.

• See: Probabilistic Graphical Model, Latent Dirichlet Allocation, Spectral Clustering, Ray Framework.

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References

• Professional Homepage: http://www.cs.berkeley.edu/~jordan/
• DBLP Author Author Page: http://dblp.uni-trier.de/db/indices/a-tree/j/Jordan:Michael_I=.html
• Google Scholar Author Page: http://scholar.google.com/scholar?q=Michael+I.+Jordan

2018

• (Jin et al., 2018) ⇒ Chi Jin, Zeyuan Allen-Zhu, Sébastien Bubeck, and Michael I. Jordan. (2018). “Is Q-learning Provably Efficient?. ” Advances in Neural Information Processing Systems 31
• (Liang et al., 2018) ⇒ Eric Liang, Richard Liaw, Philipp Moritz, Robert Nishihara, Roy Fox, Ken Goldberg, Joseph E. Gonzalez, Michael I. Jordan, and Ion Stoica. (2018). “RLlib: Abstractions for Distributed Reinforcement Learning.” In: Proceedings of Machine Learning Research.
• (Moritz et al., 2018) ⇒ Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I. Jordan, and Ion Stoica. (2018). “Ray: A Distributed Framework for Emerging AI Applications.” In: Proceedings of the 13th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 18).

2015

• (Jordan & Mitchell, 2015) ⇒ Michael I. Jordan, and Tom M. Mitchell. (2015). “Machine Learning: Trends, Perspectives, and Prospects.” In: Science Journal, 349 (6245). doi:10.1126/science.aaa8415

2014

• (Jordan, 2014a) ⇒ Michael I. Jordan. (2014). “I guess that I have to say something about "deep learning".
• Michael Jordan interview. http://spectrum.ieee.org/robotics/artificial-intelligence/machinelearning-maestro-michael-jordan-on-the-delusions-of-big-data-and-other-huge-engineering-efforts/

2013

• (Kleiner et al., 2013) ⇒ Ariel Kleiner, Ameet Talwalkar, Sameer Agarwal, Ion Stoica, and Michael I. Jordan. (2013). “A General Bootstrap Performance Diagnostic.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2487650

2010

• (Obozinski et al., 2010) ⇒ Guillaume Obozinski, Ben Taskar, and Michael I. Jordan. (2010). “Joint Covariate Selection and Joint Subspace Selection for Multiple Classification Problems.” In: Statistics and Computing Journal, 20(2). doi:10.1007/s11222-008-9111-x

2009

• (Yan et al., 2009) ⇒ Donghui Yan, Ling Huang Intel, and Michael I. Jordan. (2009). “Fast Approximate Spectral Clustering.” In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009). doi:10.1145/1557019.1557118
• (Liang, Jordan & Klein, 2009) ⇒ Percy Liang, Michael I. Jordan, and Dan Klein. (2009). “Learning Semantic Correspondences with Less Supervision.” In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP (ACL 2009).
• (Miller et al., 2009) ⇒ Kurt T. Miller, Thomas L. Griffiths, and Michael I. Jordan. (2009). “Nonparametric Latent Feature Models for Link Prediction..” In: Advances in Neural Information Processing Systems 22 (NIPS 2009).

2006

• (Teh et al., 2006) ⇒ Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, and David M. Blei. (2006). “Hierarchical Dirichlet Processes.” In: Journal of the American Statistical Association.

2005

• (Blei & Jordan, 2005) ⇒ David M. Blei, and Michael I. Jordan (2005), "Variational Methods for Dirichlet Process Mixtures.” In: Bayesian Analysis, 1.

2004

• (Blei & Jordan, 2004) ⇒ David M. Blei, and Michael I. Jordan. (2004). “Variational Methods for the Dirichlet Process.” In: Proceedings of the International Conference on Machine Learning (ICML 2004).
• (Lanckriet et al., 2004a) ⇒ Gert R. G. Lanckriet, Nello Cristianini, Peter Bartlett, Laurent El Ghaoui, and Michael I. Jordan. (2004). “Learning the Kernel Matrix with Semidefinite Programming.” In: The Journal of Machine Learning Research, 5.
• (Lanckriet et al., 2004b) ⇒ Gert R. G. Lanckriet, Tijl De Bie, Nello Cristianini, Michael I. Jordan, and William Stafford Noble. (2004). “A Statistical Framework for Genomic Data Fusion.” In: Bioinformatics, 20(16), November 2004 doi:10.1093/bioinformatics/bth294

2003

• (Blei, Ng & Jordan, 2003) ⇒ David M. Blei, Andrew Y. Ng, and Michael I. Jordan. (2003). “Latent Dirichlet Allocation.” In: The Journal of Machine Learning Research, 3. doi:10.1162/jmlr.2003.3.4-5.993
• (Xing, Ng, et al., 2003) ⇒ Eric P. Xing, Andrew Y. Ng, Michael I. Jordan and Stuart J. Russell. (2003). “Distance Metric Learning, with Application to Clustering with Side-Information.” In: Advances in Neural Information Processing Systems (NIPS 15).
• (Andrieu et al., 2003) ⇒ Christophe Andrieu, Nando De Freitas, Arnaud Doucet, and Michael I. Jordan. (2003). “An Introduction to MCMC for Machine Learning.” In: Machine Learning, 50(1). doi:10.1023/A:1020281327116
• (Wainwright & Jordan, 2003) ⇒ M. Wainwright, and Michael I. Jordan. (2003). “Graphical Models, Exponential Families, and Variational Inference.” Technical Report 649, U.C. Berkeley, Dept. of Statistics.
• (Blei, Jordan & Ng, 2003) ⇒ David M. Blei, Michael I. Jordan, and Andrew Y. Ng. (2003). “Hierarchical Bayesian Models for Applications in Information Retrieval.” In: Bayesian Statistics, 7. ISBN:0198526156
• (Blei & Jordan, 2003) ⇒ David M. Blei, and Michael I. Jordan. (2003). “Modeling Annotated Data.” In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2003).
• (Xing, Jordan & Russell, 2003) ⇒ Eric P. Xing, Michael I. Jordan, and Stuart J. Russell. (2003). “A Generalized Mean Field Algorithm for Variational Inference in Exponential Families.” In: Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI 2003).

2002

• (Xing et al., 2002a) ⇒ Eric P. Xing, Michael I. Jordan, Richard M. Karp and Stuart J. Russell. (2002). “A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences.” In: In: Proceedings of Advances in Neural Information Processing Systems.
• (Xing et al., 2002b) ⇒ Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, and Stuart J. Russell. "Distance Metric Learning, with Application to Clustering with Side-Information.” In: Advances in Neural Information Processing Systems 15 (NIPS 2002).
• (Ng et al., 2002) ⇒ Andrew Y. Ng , Michael I. Jordan, and Yair Weiss. (2002). “On Spectral Clustering: Analysis and an algorithm.” In: Advances in Neural Information Processing Systems, 14 (NIPS 2002)

2001

• (Ng & Jordan, 2001) ⇒ Andrew Y. Ng, and Michael I. Jordan. (2001). “On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes.” In: Proceeding of NIPS Conference (NIPS 2001).
• (Ng, Jordan & Weiss, 2001) ⇒ Andrew Y. Ng, Michael I. Jordan, and Yair Weiss. (2001). “On Spectral Clustering: Analysis and an algorithm.” In: Advances in Neural Information Processing Systems, 14 (NIPS 2001)
• (Blei et al., 2001) ⇒ David M. Blei, Andrew Y. Ng, and Michael I. Jordan. (2001). “Latent Dirichlet Allocation.” In: Advances in Neural Information Processing Systems (NIPS-2001)

2000

• (Jaakkola & Jordan, 2000) ⇒ Tommi S. Jaakkola, and Michael I. Jordan. (2000). “Bayesian Parameter Estimation via Variational Methods.” In: Stat. Comput., 10(1).

1999

• (Jordan et al., 1999) ⇒ Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, and Lawrence K. Saul. (1999). “An Introduction to Variational Methods for Graphical Models.” In: Machine Learning, 37(2). doi:10.1023/A:1007665907178
• (Murphy et al., 1999) ⇒ Kevin Murphy, Yair Weiss, and Michael I. Jordan. (1999). “Loopy Belief Propagation for Approximate Inference: An empirical study.” In: Proceedings of Uncertainty in AI (UAI 1999).

1998

• (Jordan, 1998) ⇒ Michael I. Jordan (editor). (1998). “Learning in Graphical Models." MIT Press. ISBN:0-262-60032-3
• (Jaakkola & Jordan, 1998) ⇒ Tommi S. Jaakkola, and Michael I. Jordan. (1998). “Improving the Mean Field Approximation Via the Use of Mixture Distributions.” In: (Jordan, 1998) "Learning in Graphical Models." MIT Press. ISBN:0-262-60032-3

1997

• (Jordan, 1997) ⇒ Michael I. Jordan. (1997). “An Introduction to Graphical Models." Tutorial at NIPS-1997.

1996

• (Saul & Jordan, 1996) ⇒ L. Saul, and Michael I. Jordan. (1996). “Boltzmann Chains and Hidden Markov Models.” In: Advances in Neural Information Processing Systems (NIPS 7).

1995

• (Ghahramani & Jordan, 1995) ⇒ Zoubin Ghahramani, and Michael I. Jordan. (1995). “Factorial Hidden Markov Models.” In: Proceedings of Advances in Neural Information Processing Systems (NIPS 8).

1994

• (Ghahramani & Jordan, 1994) ⇒ Zoubin Ghahramani, and Michael I. Jordan. (1994). “Supervised Learning from Incomplete Data Via an EM Approach.” In: Advances in Neural Information Processing Systems (NIPS 6).

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