John D. Lafferty

发表

Topic Model

Yueshen Xu, CCNT, ZJU, 2014, Encyclopedia of Social Network Analysis and Mining.

CALOREE: Learning Control for Predictable Latency and Low Energy

Henry Hoffmann, John D. Lafferty, Connor Imes, 2018, ASPLOS.

A Robust Parsing Algorithm for Link Grammars pdf

John D. Lafferty, Dennis Grinberg, Daniel Dominic Sleator, 1995, IWPT.

The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs

Larry A. Wasserman, John D. Lafferty, Han Liu, 2009, J. Mach. Learn. Res..

Cyberpunc: a lightweight punctuation annotation system for speech

John D. Lafferty, Doug Beeferman, Adam L. Berger, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

Preconditioner Approximations for Probabilistic Graphical Models

Pradeep Ravikumar, John D. Lafferty, 2005, NIPS.

Erratum to: A Statistical Approach to Machine Translation

John Cocke, John D. Lafferty, Frederick Jelinek, 1991, CL.

Multiscale topic tomography

Ramesh Nallapati, John D. Lafferty, Susan Ditmore, 2007, KDD '07.

Exponential Concentration for Mutual Information Estimation with Application to Forests

Larry A. Wasserman, John D. Lafferty, Han Liu, 2012, NIPS.

Computation-Risk Tradeoffs for Covariance-Thresholded Regression

John D. Lafferty, Dinah Shender, 2013, ICML.

Sparse Nonparametric Graphical Models pdf

Larry A. Wasserman, John D. Lafferty, Han Liu, 2012, ArXiv.

Sparse Additive Functional and Kernel CCA pdf

Sivaraman Balakrishnan, John D. Lafferty, Kriti Puniyani, 2012, ICML.

The Weaver System for Document Retrieval

John D. Lafferty, Adam L. Berger, J. Lafferty, 1999, TREC.

Fast Fourier Analysis for SL2 over a Finite Field and Related Numerical Experiments

John D. Lafferty, Daniel N. Rockmore, J. Lafferty, 1992, Exp. Math..

A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements

John D. Lafferty, Qinqing Zheng, J. Lafferty, 2015, NIPS.

Inference and Estimation of a Long-Range Trigram Model

John D. Lafferty, Stephen Della Pietra, Vincent J. Della Pietra, 1994, ICGI.

Decision Tree Models Applied to the Labeling of Text with Parts-of-Speech

John D. Lafferty, Frederick Jelinek, Robert L. Mercer, 1992, HLT.

The Bigraphical Lasso

Neil D. Lawrence, John D. Lafferty, Shuheng Zhou, 2013, ICML.

Expectation-Propogation for the Generative Aspect Model

Tom Minka, John D. Lafferty, J. Lafferty, 2002, UAI.

A Model of Lexical Attraction and Repulsion

John D. Lafferty, Doug Beeferman, Adam L. Berger, 1997, ACL.

Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent pdf

John D. Lafferty, Qinqing Zheng, J. Lafferty, 2016, ArXiv.

Information Diffusion Kernels

John D. Lafferty, Guy Lebanon, 2002, NIPS.

Document Language Models, Query Models, and Risk Minimization for Information Retrieval

John D. Lafferty, ChengXiang Zhai, J. Lafferty, 2001, SIGIR Forum.

A study of smoothing methods for language models applied to Ad Hoc information retrieval

John D. Lafferty, ChengXiang Zhai, J. Lafferty, 2001, SIGIR '01.

Information retrieval as statistical translation

John D. Lafferty, Adam L. Berger, J. Lafferty, 1999, SIGIR '99.

Cheating with imperfect transcripts

John D. Lafferty, Paul Placeway, J. Lafferty, 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

Quantized Estimation of Gaussian Sequence Models in Euclidean Balls

John D. Lafferty, Yuancheng Zhu, J. Lafferty, 2014, NIPS.

Statistical Models for Text Segmentation

John D. Lafferty, Doug Beeferman, Adam L. Berger, 1999, Machine Learning.

Dynamic topic models

John D. Lafferty, David M. Blei, J. Lafferty, 2006, ICML.

Conditional Models on the Ranking Poset

John D. Lafferty, Guy Lebanon, J. Lafferty, 2002, NIPS.

Visualizing Topics with Multi-Word Expressions

John D. Lafferty, David M. Blei, J. Lafferty, 2009, 0907.1013.

Correlated Topic Models

John D. Lafferty, David M. Blei, J. Lafferty, 2005, NIPS.

Parallelized Variational EM for Latent Dirichlet Allocation: An Experimental Evaluation of Speed and Scalability

Ramesh Nallapati, John D. Lafferty, William W. Cohen, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).

Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo

Larry A. Wasserman, John D. Lafferty, Han Liu, 2007, AISTATS.

Towards History-based Grammars: Using Richer Models for Probabilistic Parsing pdf

John D. Lafferty, Frederick Jelinek, Robert L. Mercer, 1993, ACL.

Development and Evaluation of a Broad-Coverage Probabilistic Grammar of English-Language Computer Manuals

John D. Lafferty, Salim Roukos, Ezra Black, 1992, ACL.

A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval

John D. Lafferty, ChengXiang Zhai, 2017, SIGF.

Mismatched estimation and relative entropy in vector Gaussian channels

John D. Lafferty, Minhua Chen, 2013, 2013 IEEE International Symposium on Information Theory.

Workshop on language modeling and information retrieval

W. Bruce Croft, John D. Lafferty, James P. Callan, 2001, SIGF.

Statistical Analysis of Semi-Supervised Regression

Larry A. Wasserman, John D. Lafferty, J. Lafferty, 2007, NIPS.

Cluster Expansions and Iterative Scaling for Maximum Entropy Language Models pdf

John D. Lafferty, Bernhard Suhm, J. Lafferty, 1995, ArXiv.

Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning

Xiaojin Zhu, John D. Lafferty, J. Lafferty, 2005, ICML.

Feature selection in conditional random fields for activity recognition

Manuela M. Veloso, John D. Lafferty, Douglas L. Vail, 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Nonparametric regression and classification with joint sparsity constraints

Larry A. Wasserman, John D. Lafferty, Han Liu, 2008, NIPS.

A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints

Henry Hoffmann, John D. Lafferty, Nikita Mishra, 2015, ASPLOS.

Decision Tree Parsing using a Hidden Derivation Model

John D. Lafferty, Frederick Jelinek, Robert L. Mercer, 1994, HLT.

Inducing Features of Random Fields pdf

John D. Lafferty, Stephen Della Pietra, Vincent J. Della Pietra, 1995, IEEE Trans. Pattern Anal. Mach. Intell..

Analysis, statistical transfer, and synthesis in machine translation

John D. Lafferty, Peter F. Brown, Robert, 1992, TMI.

Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002

Djoerd Hiemstra, Alan F. Smeaton, Nicholas J. Belkin, 2003, SIGF.

The Candide System for Machine Translation

John D. Lafferty, Robert L. Mercer, Peter F. Brown, 1994, HLT.

Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk

Larry A. Wasserman, John D. Lafferty, J. Lafferty, 2001, UAI.

A Statistical Approach to Machine Translation

John Cocke, John D. Lafferty, Frederick Jelinek, 1990, CL.

Nonparametric Reduced Rank Regression

John D. Lafferty, Rina Foygel, Mathias Drton, 2012, NIPS.

Hyperplane margin classifiers on the multinomial manifold

John D. Lafferty, Guy Lebanon, J. Lafferty, 2004, ICML.

Diffusion Kernels on Graphs and Other Discrete Input Spaces

John D. Lafferty, Risi Kondor, J. Lafferty, 2002, ICML.

Blossom Tree Graphical Models

Zhe Liu, John D. Lafferty, 2014, NIPS.

Combining Simple Discriminators for Object Discrimination

Martial Hebert, John D. Lafferty, Shyjan Mahamud, 2002, ECCV.

Computation of the Probability of Initial Substring Generation by Stochastic Context-Free Grammars

John D. Lafferty, Frederick Jelinek, J. Lafferty, 1991, Comput. Linguistics.

Union Support Recovery in Multi-task Learning

Larry A. Wasserman, John D. Lafferty, Mladen Kolar, 2010, J. Mach. Learn. Res..

Selective inference for group-sparse linear models

Fan Yang, Prateek Jain, John D. Lafferty, 2016, NIPS.

Semi-supervised learning using randomized mincuts

John D. Lafferty, Avrim Blum, Rajashekar Reddy, 2004, ICML.

Quadratic programming relaxations for metric labeling and Markov random field MAP estimation

Pradeep Ravikumar, John D. Lafferty, J. Lafferty, 2006, ICML.

Text Segmentation Using Exponential Models

John D. Lafferty, Doug Beeferman, Adam L. Berger, 1997, EMNLP.

Signal Decomposition using Multiscale Admixture Models

Matus Telgarsky, John D. Lafferty, J. Lafferty, 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

The Nonparanormal SKEPTIC pdf

Larry A. Wasserman, John D. Lafferty, Fang Han, 2012, ICML 2012.

Fast nonparametric matrix factorization for large-scale collaborative filtering

Yihong Gong, Shenghuo Zhu, John D. Lafferty, 2009, SIGIR.

Information Retrieval as Statistical Translation

John D. Lafferty, Adam L. Berger, J. Lafferty, 2017 .

High Dimensional Semiparametric Gaussian Copula Graphical Models.

Larry A. Wasserman, John D. Lafferty, Fang Han, 2012, ICML 2012.

SpAM: Sparse Additive Models

Larry A. Wasserman, Pradeep Ravikumar, John D. Lafferty, 2007, NIPS.

Prediction Rule Reshaping pdf

John D. Lafferty, Sabyasachi Chatterjee, Rina Foygel Barber, 2018, ICML.

Local Minimax Complexity of Stochastic Convex Optimization

John D. Lafferty, Sabyasachi Chatterjee, John C. Duchi, 2016, NIPS.

Two-stage language models for information retrieval

John D. Lafferty, ChengXiang Zhai, J. Lafferty, 2002, SIGIR '02.

Conditional Sparse Coding and Grouped Multivariate Regression

Min Xu, John D. Lafferty, J. Lafferty, 2012, ICML.

Cranking: Combining Rankings Using Conditional Probability Models on Permutations

John D. Lafferty, Guy Lebanon, J. Lafferty, 2002, ICML.

Kernel conditional random fields: representation and clique selection

Xiaojin Zhu, John D. Lafferty, Yan Liu, 2004, ICML.

High-Dimensional Graphical Model Selection Using ℓ1-Regularized Logistic Regression

Martin J. Wainwright, Pradeep Ravikumar, John D. Lafferty, 2006, NIPS.

Compressed and Privacy-Sensitive Sparse Regression

Larry A. Wasserman, John D. Lafferty, Shuheng Zhou, 2009, IEEE Transactions on Information Theory.

Diffusion Kernels on Statistical Manifolds

John D. Lafferty, Guy Lebanon, J. Lafferty, 2005, J. Mach. Learn. Res..

Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning

Zoubin Ghahramani, Xiaojin Zhu, John D. Lafferty, 2004, NIPS.

Rodeo: Sparse Nonparametric Regression in High Dimensions

Larry A. Wasserman, John D. Lafferty, J. Lafferty, 2005, NIPS.

A correlated topic model of Science

John D. Lafferty, David M. Blei, J. Lafferty, 2007, 0708.3601.

Numerical Investigation of the Spectrum for Certain Families of Cayley Graphs

John D. Lafferty, Daniel N. Rockmore, J. Lafferty, 1992, Expanding Graphs.

Spectral techniques for expander codes

John D. Lafferty, Daniel N. Rockmore, J. Lafferty, 1997, STOC '97.

Variational Chernoff Bounds for Graphical Models

Pradeep Ravikumar, John D. Lafferty, 2004, UAI.

A risk minimization framework for information retrieval

John D. Lafferty, ChengXiang Zhai, J. Lafferty, 2006, Inf. Process. Manag..

Graph-Valued Regression

Xi Chen, Larry A. Wasserman, John D. Lafferty, 2010, NIPS.

Word clustering with parallel spoken language corpora

Alexander H. Waibel, John D. Lafferty, Ye-Yi Wang, 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

Compressed Regression

Larry A. Wasserman, John D. Lafferty, Shuheng Zhou, 2007, NIPS.

Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions

Zoubin Ghahramani, Xiaojin Zhu, John D. Lafferty, 2003, ICML 2003.

Large-scale collaborative prediction using a nonparametric random effects model

Yihong Gong, Shenghuo Zhu, John D. Lafferty, 2009, ICML '09.

The huge Package for High-dimensional Undirected Graph Estimation in R

Larry A. Wasserman, John D. Lafferty, Tuo Zhao, 2012, J. Mach. Learn. Res..

Time varying undirected graphs

Larry A. Wasserman, John D. Lafferty, Shuheng Zhou, 2008, Machine Learning.

ESP: A Machine Learning Approach to Predicting Application Interference

Henry Hoffmann, John D. Lafferty, Nikita Mishra, 2017, 2017 IEEE International Conference on Autonomic Computing (ICAC).

Beyond independent relevance: methods and evaluation metrics for subtopic retrieval

John D. Lafferty, ChengXiang Zhai, William W. Cohen, 2003, SIGIR.

Boosting and Maximum Likelihood for Exponential Models

John D. Lafferty, Guy Lebanon, J. Lafferty, 2001, NIPS.

Conditional random fields for activity recognition

Manuela M. Veloso, John D. Lafferty, Douglas L. Vail, 2007, AAMAS '07.

Model-based feedback in the language modeling approach to information retrieval

John D. Lafferty, ChengXiang Zhai, J. Lafferty, 2001, CIKM '01.

Ordered Binary Decision Diagrams and Minimal Trellises

Alexander Vardy, John D. Lafferty, 1999, IEEE Trans. Computers.

Learning image representations from the pixel level via hierarchical sparse coding

John D. Lafferty, Yuanqing Lin, Kai Yu, 2011, CVPR 2011.

Sequential Nonparametric Regression pdf

John D. Lafferty, Haijie Gu, J. Lafferty, 2012, ICML.

Computationally Efficient M-Estimation of Log-Linear Structure Models

Noah A. Smith, John D. Lafferty, Douglas L. Vail, 2007, ACL.

Probabilistic Decoding of Low-Density Cayley Codes

John D. Lafferty, Adam L. Berger, J. Lafferty, 2022 .

Correction: A correlated topic model of Science

John D. Lafferty, David M. Blei, J. Lafferty, 2007, 0712.1486.