John Lafferty

Publications
2006 High-Dimensional Graphical Model Selection Using l₁-Regularized Logistic Regression Martin Wainwright, Pradeep Ravikumar, and John Lafferty In Advances in Neural Information Processing Systems (NIPS), 19, 2006 PDF Dynamic Topic Models David Blei and John Lafferty Machine Learning: Proceedings of the Twenty-Third International Conference (ICML), 2006 PDF Quadratic programming relaxations for metric labeling and Markov random field MAP estimation Pradeeep Ravikumar and John Lafferty Machine Learning: Proceedings of the Twenty-Third International Conference (ICML), 2006 PDF Challenges in Statistical Machine Learning John Lafferty and Larry Wasserman Statistica Sinica Volume 16, Number 2, pp. 307-323, 2006 PDF Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo Han Liu, John Lafferty, and Larry Wasserman Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS), 2007 PDF Conditional Random Fields for Activity Recognition Douglas Vail, Manuela Veloso, and John Lafferty International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2007 PDF Rodeo: Sparse nonparametric regression in high dimensions John Lafferty and Larry Wasserman math.ST/0506342 (revised version) Graph Kernels by Spectral Transforms Xiaojin Zhu, Jaz Kandola, John Lafferty and Zoubin Ghahramani In Semi-Supervised Learning, eds. Olivier Chapelle, Bernhard Scholkopf, and Alexander Zien, The MIT Press, 2006. PDF 2005 Correlated Topic Models David Blei and John Lafferty In Advances in Neural Information Processing Systems (NIPS), 18, 2005 PDF Preconditioner Approximations for Probabilistic Graphical Models Pradeeep Ravikumar and John Lafferty In Advances in Neural Information Processing Systems (NIPS), 18, 2005 postscript PDF Rodeo: Sparse nonparametric regression in high dimensions John Lafferty and Larry Wasserman In Advances in Neural Information Processing Systems (NIPS), 18, 2005 Long version submitted for publication postscript PDF Person identification in webcam images: An application of semi-supervised learning Maria-Florina Balcan, Avrim Blum, Pakyan Choi, John Lafferty, Brian Pantano, Mugizi Robert Rwebangira and Xiaojin Zhu ICML 2005 Workshop on Learning with Partially Classified Training Data PDF Harmonic mixtures: Combining mixture models and graph-based methods for inductive and scalable semi-supervised learning Xiaojin Zhu and John Lafferty Machine Learning: Proceedings of the Twenty-Second International Conference (ICML), 2004 PDF Diffusion kernels on statistical manifolds John Lafferty and Guy Lebanon Journal of Machine Learning Research, Vol. 6, pp. 129-163, 2005 PDF link 2004 Nonparametric transforms of graph kernels for semi-supervised learning Xiaojin Zhu, Jaz Kandola, Zoubin Ghahramani and John Lafferty Advances in Neural Information Processing Systems (NIPS), 17, 2004 postscript PDF Variational Chernoff bounds for graphical models Pradeep Ravikumar and John Lafferty Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI), 2004 PDF postscript Kernel conditional random fields: Representation and clique selection John Lafferty, Xiaojin Zhu, and Yan Liu Machine Learning: Proceedings of the Twenty-First International Conference (ICML), 2004 postscript Hyperplane margin classifiers on the multinomial manifold Guy Lebanon and John Lafferty Machine Learning: Proceedings of the Twenty-First International Conference (ICML), 2004 PDF postscript Semi-supervised learning using randomized mincuts Avrim Blum, John Lafferty, Rajashekar Reddy, and Mugizi Robert Rwebangira Machine Learning: Proceedings of the Twenty-First International Conference (ICML), 2004 postscript A risk minimization framework for information retrieval ChengXiang Zhai and John Lafferty Information Processing and Management, to appear. postscript PDF Mixed membership models of scientific publications Elena Erosheva, Steve Fienberg, and John Lafferty Proceedings of the National Academy of Sciences, Vol. 101, Suppl. 1, April 6, 2004 ( PNAS site) PDF A study of smoothing methods for language models applied to information retrieval ChengXiang Zhai and John Lafferty ACM Transactions on Information Systems, Vol. 2, Issue 2, April 2004 postscript 2003 Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions Xiaojin Zhu, John Lafferty and Zoubin Ghahramani ICML 2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining postscript Semi-supervised learning: From Gaussian fields to Gaussian processes Xiaojin Zhu, John Lafferty and Zoubin Ghahramani Technical Report CMU-CS-03-175, School of Computer Science, CMU, 2003 link Semi-supervised learning using Gaussian fields and harmonic functions Xiaojin Zhu, Zoubin Ghahramani and John Lafferty Machine Learning: Proceedings of the Twentieth International Conference, 2003 postscript Beyond independent relevance: Methods and evaluation metrics for subtopic retrieval ChengXiang Zhai, William Cohen, and John Lafferty Proceedings of ACM SIGIR, 2003 postscript Eigenvalue spacings for quantized cat maps Alexander Gamburd, John Lafferty, and Dan Rockmore Journal of Physics A: Mathematical and General, 36 (2003), Special Issue: Random Matrix Theory [IoP site] postscript Language Modeling for Information Retrieval W. Bruce Croft and John Lafferty, editors Kluwer International Series on Information Retrieval, Vol. 13, 2003 [Kluwer site] Probabilistic relevance models based on document and query generation John Lafferty and Chengxiang Zhai Language Modeling for Information Retrieval, Kluwer International Series on Information Retrieval, Vol. 13, 2003 postscript 2002 Conditional models on the ranking poset Guy Lebanon and John Lafferty Advances in Neural Information Processing Systems (NIPS), 15, 2002 postscript Information diffusion kernels John Lafferty and Guy Lebanon Advances in Neural Information Processing Systems (NIPS), 15, 2002 postscript Expectation-propagation for the generative aspect model Thomas Minka and John Lafferty Uncertainty in Artificial Intelligence (UAI), 2002 postscript Two-stage language models for information retrieval Chengxiang Zhai and John Lafferty 2002 ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2002 postscript Diffusion kernels on graphs and other discrete input spaces Risi Imre Kondor and John Lafferty Machine Learning: Proceedings of the Nineteenth International Conference, San Mateo, CA: Morgan Kaufmann, 2002 postscript Cranking: Combining rankings using conditional probability models on permutations Guy Lebanon and John Lafferty Machine Learning: Proceedings of the Nineteenth International Conference, San Mateo, CA: Morgan Kaufmann, 2002 postscript 2001 Boosting and maximum likelihood for exponential models Guy Lebanon and John Lafferty In Advances in Neural Information Processing Systems (NIPS), 14, 2001 Longer version: Technical Report CMU-CS-01-144, School of Computer Science, CMU, 2001 postscript Duality and auxiliary functions for Bregman distances Stephen Della Pietra, Vincent Della Pietra, and John Lafferty Technical Report CMU-CS-01-109, School of Computer Science, CMU, 2001 link Conditional random fields: Probabilistic models for segmenting and labeling sequence data John Lafferty, Andrew McCallum, and Fernando Pereira International Conference on Machine Learning (ICML), 2001 postscript Iterative Markov chain Monte Carlo computation of reference priors and minimax risk John Lafferty and Larry Wasserman Uncertainty in Artificial Intelligence (UAI), 2001 postscript Model-based feedback in the language modeling approach to information retrieval Chengxiang Zhai and John Lafferty Tenth International ACM Conference on Information and Knowledge Management (CIKM'01), 2001 postscript Document language models, query models, and risk minimization for information retrieval John Lafferty and Chengxiang Zhai 2001 ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2001 postscript A study of smoothing methods for language models applied to ad hoc information retrieval Chengxiang Zhai and John Lafferty 2001 ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2001 postscript Codes and iterative decoding on algebraic expander graphs John Lafferty and Daniel Rockmore International Symposium on Information Theory and its Application, Honolulu, Hawaii, 2000 postscript Earlier Additive models, boosting, and inference for generalized divergences John Lafferty Proceedings of the Twelfth Annual Conference on Computational Learning Theory (COLT'99), 1999 postscript Information retrieval as statistical translation Adam Berger and John Lafferty 1999 ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'99) postscript The Weaver system for document retrieval Adam Berger and John Lafferty Proceedings of TREC-8, Gaithersburg, MD, 1999 postscript Using maximum entropy for text classification Kamal Nigam, John Lafferty, and Andrew McCallum Proceedings of the IJCAI-99 Workshop on Machine Learning for Information Filtering, 1999 postscript Statistical models for text segmentation Doug Beeferman, Adam Berger, and John Lafferty Machine Learning, special issue on Natural Language Learning, C. Cardie and R. Mooney eds., 34(1-3), pp. 177-210, 1999 postscript Ordered binary decision diagrams and minimal trellises John Lafferty and Alexander Vardy IEEE Trans. Computers, Vol. 48, No. 9, pp. 971-986, Sept., 1999 postscript Level spacings for Cayley graphs John Lafferty and Daniel Rockmore In Emerging Applications of Number Theory, D. Hejhal, J. Friedman, M. Gutzwiller, and A. Odlyzko, eds., The IMA Volumes in Mathematics and its Applications, Vol. 109, 1998 postscript Spectral techniques for expander codes John Lafferty and Daniel Rockmore ACM Symposium on Theory of Computing (STOC), 1997, pp. 160-167 postscript Spectral techniques for expander codes and generalized cyclic codes John Lafferty and Daniel Rockmore 1997 IEEE International Symposium on Information Theory, Ulm Germany postscript Inducing features of random fields Stephen Della Pietra, Vincent Della Pietra, and John Lafferty IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(4), April 1997, pp. 380-393 postscript Statistical learning algorithms based on Bregman distances John Lafferty, Stephen Della Pietra and Vincent Della Pietra Proceedings of 1997 Canadian Workshop on Information Theory, Fields Institute, Toronto, Canada, pp. 77-80 postscript Text segmentation using exponential models Doug Beeferman, Adam Berger and John Lafferty Second Conference on Empirical Methods in Natural Language Processing, 1997 postscript Cyberpunc: A lightweight punctuation annotation system for speech Doug Beeferman, Adam Berger and John Lafferty IEEE Conference on Acoustic, Speech, and Signal Processing, 1998 postscript A model of lexical attraction and repulsion Doug Beeferman, Adam Berger and John Lafferty Proceedings of 1997 ACL-EACL Joint Conferences, Madrid, Spain, pp. 373-380 postscript Gibbs-Markov models John Lafferty Computing Science and Statistics, 27, 370-377, 1996 postscript Cluster expansions and iterative scaling for maximum entropy language models John Lafferty and Bernhard Suhm Maximum Entropy and Bayesian Methods, K. Hanson and R. Silver, eds., Kluwer Academic Publishers, 1996 postscript A robust parsing algorithm for link grammars Dennis Grinberg, John Lafferty and Daniel Sleator Proceedings of the Fourth International Workshop on Parsing Technologies, 1995 Also issued as CMU technical report CMU-CS-95-125 postscript Phase space density and fluid flow: Conservation laws and a Boltzmann equation associated with the stochastic Newton equation John Lafferty and Charles Peskin Stochastic Processes, Geometry, and Physics II, S. Albeverio, U. Cattaneo, and D. Merlini, eds., World Scientific, 1995 Decision tree parsing using a hidden derivation model Frederick Jelinek, John Lafferty, David Magerman, Robert Mercer, Adwait Ratnaparkhi and Salim Roukos Human Language Technology, Proceedings of the ARPA Workshop on Speech and Natural Language, Morgan Kaufman Publishers, 1994 Inference and estimation of a long-range trigram model Stephen Della Pietra, Vincent Della Pietra, John Gillett, John Lafferty, Harry Printz, Lubos Ures Second International Colloquium on Grammatical Inference and Applications, Lecture Notes in Artificial Intelligence, 862 (1994), Springer-Verlag, 78-92 The Candide system for machine translation Adam Berger, Peter Brown, Stephen Della Pietra, Vincent Della Pietra, John Gillett, John Lafferty, Robert Mercer, Harry Printz, Lubos Ures Human Language Technology, Proceedings of the ARPA Workshop on Speech and Natural Language, Morgan Kaufman Publishers, 1994 postscript Numerical investigation of the spectrum for certain families of Cayley graphs John Lafferty and Daniel Rockmore DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Volume 10, 1993, 63-73 postscript Automatic word classification using features of spellings John Lafferty and Robert Mercer 9th Conference of the University of Waterloo Centre for the New OED and Text Research Oxford University Press, Oxford England, 1993. *Fast Fourier analysis for SL₂* over a finite field and related numerical experiments** John Lafferty and Daniel Rockmore Experimental Mathematics, 1:115-139, 1992 [gzipped postscript] PDF A direct geometric proof of the Lefschetz fixed point formulas John Lafferty, Yanlin Yu, and Weiping Zhang Trans. Amer. Math. Soc., 329(2): 571-582, 1992 postscript link to PDF Grammatical trigrams: A probabilistic model of link grammar John Lafferty, Daniel Sleator and Davy Temperley AAAI Fall Symposium on Probabilistic Approaches to Natural Language Cambridge, MA, October 1992 Technical report CMU-CS-92-181, Department of Computer Science, CMU postscript Analysis, statistical transfer, and synthesis in machine translation Peter F. Brown, Vincent Della Pietra, Stephen Della Pietra, John D. Lafferty, Robert L. Mercer Proceedings of the Fourth International Conference on Theoretical and Methodological Aspects of Machine Translation, pp. 83-100, 1992 postscript Decision tree models applied to the labeling of text with parts of speech Ezra Black, Frederick Jelinek, John Lafferty, Robert Mercer, and Salim Roukos Proceedings of the DARPA Speech and Natural Language Workshop, Arden House, February 1992. Towards history-based grammars: Using richer models for probabilistic parsing Ezra Black, Frederick Jelinek, John Lafferty, David Magerman, Robert Mercer, and Salim Roukos Proceedings of the DARPA Speech and Natural Language Workshop, Arden House, February 1992. PDF Computation of the probability of initial substring generation by stochastic context-free grammars Frederick Jelinek and John Lafferty Computational Linguistics, 17(3), pp. 315-323, 1991 PDF A statistical approach to machine translation Peter F. Brown, John Cocke, Vincent Della Pietra, Stephen Della Pietra, Frederick Jelinek, John D. Lafferty, Robert L. Mercer, and Paul S. Roossin Computational Linguistics, 6(2), pp. 79-85, 1990 postscript PDF Clifford asymptotics and the local Lefschetz index John Lafferty, Yanlin Yu, and Weiping Zhang Topological Fixed Point Theory and Applications Springer Lecture Notes in Mathematics, Vol. 1411, pp. 137-142, 1989 The density manifold and configuration space quantization John Lafferty Trans. Amer. Math. Soc., 305(2), 1988 link to PDF