Publications
2010
- Graph-valued regression
Han Liu, Xi Chen, John Lafferty and Larry Wasserman
Advances in Neural Information Processing Systems 23, pp 1423-1431, 2010
pdf arxiv - High dimensional Ising
model selection using ℓ1-regularized logistic regression
Pradeep Ravikumar, Martin Wainwright and John Lafferty
Ann. Statist., Vol. 38, No. 3, pp 1287-1319, 2010
link - Union support recovery in multi-task learning
Mladen Kolar, John Lafferty and Larry Wasserman
arXiv:1008.5211 - Forest density estimation
Han Lu, Min Xu, Haijie Gu, Anupam Gupta, John Lafferty and Larry Wasserman
arXiv:1001.1557, 2010 (preliminary version in COLT 2010) - Time varying undirected graphs
Shuheng Zhou, John Lafferty and Larry Wasserman
Machine Learning, Volume 80, Numbers 2-3, September 2010, pp. 295-319.
link
2009
- Topic models
David Blei and John Lafferty
Text Mining: Classification, Clustering, and Applications Srivastava, A. and Sahami, M., Eds), Taylor & Francis, London, England, 2009.
pdf - The nonparanormal: Semiparametric estimation
of high dimensional undirected graphs
Han Liu, John Lafferty and Larry Wasserman
Journal of Machine Learning Research, Volume 10, pp 2295-2328, 2009.
pdf - Sparse additive models
Pradeep Ravikumar, John Lafferty, Han Liu and Larry Wasserman
Journal of the Royal Statistical Society, Series B, (Statistical Methodology) Vol. 71, Issue 5, pp 1009-1030, November 2009.
link pdf - Large-scale collaborative prediction using a nonparametric
random effects model
Kai Yu, John Lafferty, Shenghuo Zhu and Yihong Gong
Machine Learning: Proceedings of the Twenty-Sixth International Conference (ICML), 2009
pdf - Fast nonparametric matrix factorization for large-scale
collaborative filtering
Kai Yu, Shenghuo Zhu, John Lafferty and Yihong Gong
2009 ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2009
pdf - Visualizing topics with multiword expressions
David Blei and John Lafferty
arXiv:0907.1013
2008
- Nonparametric regression and classification with joint
sparsity constraints
Han Liu, John Lafferty and Larry Wasserman
In Advances in Neural Information Processing Systems (NIPS), 21, 2008
pdf - High-dimensional Ising model selection using
l1-regularized logistic regression
Pradeep Ravikumar, Martin Wainwright, and John Lafferty
Technical Report, Department of Statistics, University of California, Berkeley.
To appear in The Annals of Statistics.
pdf - Time varying undirected graphs
Shuheng Zhou, John Lafferty and Larry Wasserman
Conference on Learning Theory (COLT), 2008
pdf - Compressed and privacy sensitive sparse regression
Shuheng Zhou, John Lafferty and Larry Wasserman
IEEE Transactions on Information Theory, Volume,55, Issue 2, pp 846-866, 2009
link, arxiv - Rodeo: sparse, greedy nonparametric regression
John Lafferty and Larry Wasserman
The Annals of Statistics, Vol. 36, No.1, 2008, pages 28-63
pdf
2007
- Comments on: Nonparametric
inference with generalized likelihood tests: Nonparametric sparsity
John Lafferty and Larry Wasserman
Test, Vol. 16, pp. 453--455, 2007. - SpAM: Sparse additive models
Pradeep Ravikumar, Han Liu, John Lafferty and Larry Wasserman
In Advances in Neural Information Processing Systems (NIPS), 20, 2007
pdf - Statistical analysis of semisupervised regression
John Lafferty and Larry Wasserman
In Advances in Neural Information Processing Systems (NIPS), 20, 2007
pdf - Compressed regression
Shuheng Zhou, John Lafferty and Larry Wasserman
In Advances in Neural Information Processing Systems (NIPS), 20, 2007
pdf - Computationally efficient M-estimation of log-linear
structure models
Noah Smith, John Laferty and Doug Vail
in Proceedings of Conference of the Association for Computational Linguistics, 2007
pdf - A correlated topic model of Science
David Blei and John Lafferty
Annals of Applied Statistics, Vol. 1, No. 1, 17-35, 2007
pdf - Multiscale topic tomography
Ramesh Nallapati, William Cohen, Susan Ditmore, John Lafferty and Kin Ung
KDD'07, San Jose California, 2007
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 - Parallelized variational EM for latent Dirichlet allocation: An
experimental evaluation of speed and scalability
Ramesh Nallapati, William Cohen and John Lafferty
ICDM Workshop on High Performance Data Mining, 2007
pdf
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 - 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