John D. Lafferty

121 papers A* 35A 7B 1Misc 1Journal 40Unranked 35

Year	Rank	Type	Title / Venue / Authors
2019	A*	`conf`	TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts. AAAI Michihiro Yasunaga, John D. Lafferty
2018	A*	`conf`	CALOREE: Learning Control for Predictable Latency and Low Energy. ASPLOS Nikita Mishra, Connor Imes, John D. Lafferty, Henry Hoffmann
2018	J	`jnl`	Denoising Flows on Trees. IEEE Trans. Inf. Theory Sabyasachi Chatterjee, John D. Lafferty
2018	J	`jnl`	Distributed Nonparametric Regression under Communication Constraints. CoRR Yuancheng Zhu, John D. Lafferty
2018	J	`jnl`	Prediction Rule Reshaping. CoRR Matt Bonakdarpour, Sabyasachi Chatterjee, Rina Foygel Barber, John D. Lafferty
2017	J	`jnl`	A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval. SIGIR Forum ChengXiang Zhai, John D. Lafferty
2017	J	`jnl`	Document Language Models, Query Models, and Risk Minimization for Information Retrieval. SIGIR Forum John D. Lafferty, ChengXiang Zhai
2017	—	`conf`	ESP: A Machine Learning Approach to Predicting Application Interference. ICAC Nikita Mishra, John D. Lafferty, Henry Hoffmann
2017	J	`jnl`	Information Retrieval as Statistical Translation. SIGIR Forum Adam L. Berger, John D. Lafferty
2016	J	`jnl`	Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent. CoRR Qinqing Zheng, John D. Lafferty
2016	—	`conf`	Local Minimax Complexity of Stochastic Convex Optimization. NIPS Sabyasachi Chatterjee, John C. Duchi, John D. Lafferty, Yuancheng Zhu
2016	—	`conf`	Selective inference for group-sparse linear models. NIPS Fan Yang, Rina Foygel Barber, Prateek Jain, John D. Lafferty
2015	—	`conf`	A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements. NIPS Qinqing Zheng, John D. Lafferty
2015	J	`jnl`	A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements. CoRR Qinqing Zheng, John D. Lafferty
2015	A*	`conf`	A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints. ASPLOS Nikita Mishra, Huazhe Zhang, John D. Lafferty, Henry Hoffmann
2015	J	`jnl`	Beyond Independent Relevance: Methods and Evaluation Metrics for Subtopic Retrieval. SIGIR Forum ChengXiang Zhai, William W. Cohen, John D. Lafferty
2014	—	`conf`	Blossom Tree Graphical Models. NIPS Zhe Liu, John D. Lafferty
2014	—	`conf`	Quantized Estimation of Gaussian Sequence Models in Euclidean Balls. NIPS Yuancheng Zhu, John D. Lafferty
2013	—	`conf`	Computation-Risk Tradeoffs for Covariance-Thresholded Regression. ICML (3) Dinah Shender, John D. Lafferty
2013	J	`jnl`	Expectation-Propogation for the Generative Aspect Model CoRR Thomas P. Minka, John D. Lafferty
2013	J	`jnl`	Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk CoRR John D. Lafferty, Larry A. Wasserman
2013	B	`conf`	Mismatched estimation and relative entropy in vector Gaussian channels. ISIT Minhua Chen, John D. Lafferty
2013	—	`conf`	The Bigraphical Lasso. ICML (3) Alfredo A. Kalaitzis, John D. Lafferty, Neil D. Lawrence, Shuheng Zhou
2012	A*	`conf`	Conditional Sparse Coding and Grouped Multivariate Regression. ICML Min Xu, John D. Lafferty
2012	—	`conf`	Exponential Concentration for Mutual Information Estimation with Application to Forests. NIPS Han Liu, John D. Lafferty, Larry A. Wasserman
2012	A*	`conf`	High Dimensional Semiparametric Gaussian Copula Graphical Models. ICML Han Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman
2012	—	`conf`	Nonparametric Reduced Rank Regression. NIPS Rina Foygel, Michael Horrell, Mathias Drton, John D. Lafferty
2012	A*	`conf`	Sequential Nonparametric Regression. ICML Haijie Gu, John D. Lafferty
2012	J	`jnl`	Sequential Nonparametric Regression. CoRR Haijie Gu, John D. Lafferty
2012	J	`jnl`	Sparse Additive Functional and Kernel CCA CoRR Sivaraman Balakrishnan, Kriti Puniyani, John D. Lafferty
2012	A*	`conf`	Sparse Additive Functional and Kernel CCA. ICML Sivaraman Balakrishnan, Kriti Puniyani, John D. Lafferty
2012	J	`jnl`	Sparse Nonparametric Graphical Models CoRR John D. Lafferty, Han Liu, Larry A. Wasserman
2012	J	`jnl`	The Nonparanormal SKEPTIC. CoRR Han Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman
2012	J	`jnl`	The huge Package for High-dimensional Undirected Graph Estimation in R. J. Mach. Learn. Res. Tuo Zhao, Han Liu, Kathryn Roeder, John D. Lafferty, Larry A. Wasserman
2012	J	`jnl`	Variational Chernoff Bounds for Graphical Models CoRR Pradeep Ravikumar, John D. Lafferty
2011	J	`jnl`	Forest Density Estimation. J. Mach. Learn. Res. Han Liu, Min Xu, Haijie Gu, Anupam Gupta, John D. Lafferty, Larry A. Wasserman
2011	A*	`conf`	Learning image representations from the pixel level via hierarchical sparse coding. CVPR Kai Yu, Yuanqing Lin, John D. Lafferty
2011	J	`jnl`	Union Support Recovery in Multi-task Learning. J. Mach. Learn. Res. Mladen Kolar, John D. Lafferty, Larry A. Wasserman
2010	—	`ed.`	Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, Vancouver, British Columbia, Canada. NIPS John D. Lafferty, Christopher K. I. Williams, John Shawe-Taylor, Richard S. Zemel, Aron Culotta
2010	A*	`conf`	Forest Density Estimation. COLT Anupam Gupta, John D. Lafferty, Han Liu, Larry A. Wasserman, Min Xu
2010	—	`conf`	Graph-Valued Regression. NIPS Han Liu, Xi Chen, John D. Lafferty, Larry A. Wasserman
2010	J	`jnl`	Time varying undirected graphs. Mach. Learn. Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2009	—	`ed.`	Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, Vancouver, British Columbia, Canada. NIPS Yoshua Bengio, Dale Schuurmans, John D. Lafferty, Christopher K. I. Williams, Aron Culotta
2009	J	`jnl`	Compressed and Privacy-Sensitive Sparse Regression. IEEE Trans. Inf. Theory Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2009	A*	`conf`	Fast nonparametric matrix factorization for large-scale collaborative filtering. SIGIR Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gong
2009	A*	`conf`	Large-scale collaborative prediction using a nonparametric random effects model. ICML Kai Yu, John D. Lafferty, Shenghuo Zhu, Yihong Gong
2009	J	`jnl`	The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs. J. Mach. Learn. Res. Han Liu, John D. Lafferty, Larry A. Wasserman
2008	—	`conf`	Nonparametric regression and classification with joint sparsity constraints. NIPS Han Liu, John D. Lafferty, Larry A. Wasserman
2008	A*	`conf`	Time Varying Undirected Graphs. COLT Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2007	J	`jnl`	Compressed Regression CoRR Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2007	—	`conf`	Compressed Regression. NIPS Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
2007	A*	`conf`	Computationally Efficient M-Estimation of Log-Linear Structure Models. ACL Noah A. Smith, Douglas L. Vail, John D. Lafferty
2007	A	`conf`	Conditional random fields for activity recognition. AAMAS Douglas L. Vail, Manuela M. Veloso, John D. Lafferty
2007	A	`conf`	Feature selection in conditional random fields for activity recognition. IROS Douglas L. Vail, John D. Lafferty, Manuela M. Veloso
2007	A*	`conf`	Multiscale topic tomography. KDD Ramesh Nallapati, Susan Ditmore, John D. Lafferty, Kin Ung
2007	—	`conf`	Parallelized Variational EM for Latent Dirichlet Allocation: An Experimental Evaluation of Speed and Scalability. ICDM Workshops Ramesh Nallapati, William W. Cohen, John D. Lafferty
2007	—	`conf`	Signal Decomposition using Multiscale Admixture Models. ICASSP (2) Matus Telgarsky, John D. Lafferty
2007	—	`conf`	SpAM: Sparse Additive Models. NIPS Pradeep Ravikumar, Han Liu, John D. Lafferty, Larry A. Wasserman
2007	A	`conf`	Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo. AISTATS Han Liu, John D. Lafferty, Larry A. Wasserman
2007	—	`conf`	Statistical Analysis of Semi-Supervised Regression. NIPS John D. Lafferty, Larry A. Wasserman
2006	J	`jnl`	A risk minimization framework for information retrieval. Inf. Process. Manag. ChengXiang Zhai, John D. Lafferty
2006	A*	`conf`	Dynamic topic models. ICML David M. Blei, John D. Lafferty
2006	—	`conf`	High-Dimensional Graphical Model Selection Using ℓ NIPS Martin J. Wainwright, Pradeep Ravikumar, John D. Lafferty
2006	A*	`conf`	Quadratic programming relaxations for metric labeling and Markov random field MAP estimation. ICML Pradeep Ravikumar, John D. Lafferty
2005	—	`conf`	Correlated Topic Models. NIPS David M. Blei, John D. Lafferty
2005	J	`jnl`	Diffusion Kernels on Statistical Manifolds. J. Mach. Learn. Res. John D. Lafferty, Guy Lebanon
2005	A*	`conf`	Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning. ICML Xiaojin Zhu, John D. Lafferty
2005	—	`conf`	Preconditioner Approximations for Probabilistic Graphical Models. NIPS Pradeep Ravikumar, John D. Lafferty
2005	—	`conf`	Rodeo: Sparse Nonparametric Regression in High Dimensions. NIPS John D. Lafferty, Larry A. Wasserman
2004	J	`jnl`	A study of smoothing methods for language models applied to information retrieval. ACM Trans. Inf. Syst. ChengXiang Zhai, John D. Lafferty
2004	A*	`conf`	Hyperplane margin classifiers on the multinomial manifold. ICML Guy Lebanon, John D. Lafferty
2004	A*	`conf`	Kernel conditional random fields: representation and clique selection. ICML John D. Lafferty, Xiaojin Zhu, Yan Liu
2004	—	`conf`	Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning. NIPS Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, John D. Lafferty
2004	A*	`conf`	Semi-supervised learning using randomized mincuts. ICML Avrim Blum, John D. Lafferty, Mugizi Robert Rwebangira, Rajashekar Reddy
2004	A	`conf`	Variational Chernoff Bounds for Graphical Models. UAI Pradeep Ravikumar, John D. Lafferty
2003	A*	`conf`	Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. SIGIR ChengXiang Zhai, William W. Cohen, John D. Lafferty
2003	J	`jnl`	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. SIGIR Forum James Allan, Jay Aslam, Nicholas J. Belkin, Chris Buckley, James P. Callan, W. Bruce Croft, Susan T. Dumais, Norbert Fuhr, Donna Harman, David J. Harper, Djoerd Hiemstra, Thomas Hofmann, Eduard H. Hovy, Wessel Kraaij, John D. Lafferty, Victor Lavrenko, David D. Lewis, Liz Liddy, R. Manmatha, Andrew McCallum, Jay M. Ponte, John M. Prager, Dragomir R. Radev, Philip Resnik, Stephen E. Robertson, Ronald Rosenfeld, Salim Roukos, Mark Sanderson, Richard M. Schwartz, Amit Singhal, Alan F. Smeaton, Howard R. Turtle, Ellen M. Voorhees, Ralph M. Weischedel, Jinxi Xu, ChengXiang Zhai
2003	A*	`conf`	Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions. ICML Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
2002	—	`conf`	Combining Simple Discriminators for Object Discrimination. ECCV (3) Shyjan Mahamud, Martial Hebert, John D. Lafferty
2002	—	`conf`	Conditional Models on the Ranking Poset. NIPS Guy Lebanon, John D. Lafferty
2002	A*	`conf`	Cranking: Combining Rankings Using Conditional Probability Models on Permutations. ICML Guy Lebanon, John D. Lafferty
2002	A*	`conf`	Diffusion Kernels on Graphs and Other Discrete Input Spaces. ICML Risi Kondor, John D. Lafferty
2002	A	`conf`	Expectation-Propogation for the Generative Aspect Model. UAI Thomas P. Minka, John D. Lafferty
2002	—	`conf`	Information Diffusion Kernels. NIPS John D. Lafferty, Guy Lebanon
2002	A*	`conf`	Two-stage language models for information retrieval. SIGIR ChengXiang Zhai, John D. Lafferty
2001	A*	`conf`	A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval. SIGIR ChengXiang Zhai, John D. Lafferty
2001	—	`conf`	Boosting and Maximum Likelihood for Exponential Models. NIPS Guy Lebanon, John D. Lafferty
2001	A*	`conf`	Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. ICML John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira
2001	A*	`conf`	Document Language Models, Query Models, and Risk Minimization for Information Retrieval. SIGIR John D. Lafferty, ChengXiang Zhai
2001	A	`conf`	Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk. UAI John D. Lafferty, Larry A. Wasserman
2001	A	`conf`	Model-based Feedback in the Language Modeling Approach to Information Retrieval. CIKM ChengXiang Zhai, John D. Lafferty
2001	J	`jnl`	Workshop on language modeling and information retrieval. SIGIR Forum W. Bruce Croft, James P. Callan, John D. Lafferty
1999	A*	`conf`	Additive Models, Boosting, and Inference for Generalized Divergences. COLT John D. Lafferty
1999	A*	`conf`	Information Retrieval as Statistical Translation. SIGIR Adam L. Berger, John D. Lafferty
1999	J	`jnl`	Ordered Binary Decision Diagrams and Minimal Trellises. IEEE Trans. Computers John D. Lafferty, Alexander Vardy
1999	J	`jnl`	Statistical Models for Text Segmentation. Mach. Learn. Doug Beeferman, Adam L. Berger, John D. Lafferty
1999	—	`conf`	The Weaver System for Document Retrieval. TREC Adam L. Berger, John D. Lafferty
1998	Misc	`conf`	Cyberpunc: a lightweight punctuation annotation system for speech. ICASSP Doug Beeferman, Adam L. Berger, John D. Lafferty
1997	J	`jnl`	A Model of Lexical Attraction and Repulsion CoRR Doug Beeferman, Adam L. Berger, John D. Lafferty
1997	A*	`conf`	A Model of Lexical Attraction and Repulsion. ACL Doug Beeferman, Adam L. Berger, John D. Lafferty
1997	J	`jnl`	Inducing Features of Random Fields. IEEE Trans. Pattern Anal. Mach. Intell. Stephen Della Pietra, Vincent J. Della Pietra, John D. Lafferty
1997	A*	`conf`	Spectral Techniques for Expander Codes. STOC John D. Lafferty, Daniel N. Rockmore
1997	J	`jnl`	Text Segmentation Using Exponential Models CoRR Doug Beeferman, Adam L. Berger, John D. Lafferty
1997	A*	`conf`	Text Segmentation Using Exponential Models. EMNLP Doug Beeferman, Adam L. Berger, John D. Lafferty
1996	—	`conf`	Cheating with imperfect transcripts. ICSLP Paul Placeway, John D. Lafferty
1996	—	`conf`	Word clustering with parallel spoken language corpora. ICSLP Ye-Yi Wang, John D. Lafferty, Alex Waibel
1995	J	`jnl`	A Robust Parsing Algorithm For Link Grammars CoRR Dennis Grinberg, John D. Lafferty, Daniel Dominic Sleator
1995	J	`jnl`	Cluster Expansions and Iterative Scaling for Maximum Entropy Language Models CoRR John D. Lafferty, Bernhard Suhm
1995	J	`jnl`	Inducing Features of Random Fields CoRR Stephen Della Pietra, Vincent J. Della Pietra, John D. Lafferty
1994	—	`conf`	Decision Tree Parsing using a Hidden Derivation Model. HLT Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, Adwait Ratnaparkhi, Salim Roukos
1994	—	`conf`	Inference and Estimation of a Long-Range Trigram Model. ICGI Stephen Della Pietra, Vincent J. Della Pietra, John R. Gillett, John D. Lafferty, Harry Printz, Lubos Ures
1994	—	`conf`	The Candide System for Machine Translation. HLT Adam L. Berger, Peter F. Brown, Stephen Della Pietra, Vincent J. Della Pietra, John R. Gillett, John D. Lafferty, Robert L. Mercer, Harry Printz, Lubos Ures
1994	J	`jnl`	Towards History-based Grammars: Using Richer Models for Probabilistic Parsing. CoRR Ezra Black, Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, Salim Roukos
1993	A*	`conf`	Towards History-Based Grammars: Using Richer Models for Probabilistic Parsing. ACL Ezra Black, Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, Salim Roukos
1992	—	`conf`	Decision Tree Models Applied to the Labeling of Text with Parts-of-Speech. HLT Ezra Black, Frederick Jelinek, John D. Lafferty, Robert L. Mercer, Salim Roukos
1992	A*	`conf`	Development and Evaluation of a Broad-Coverage Probabilistic Grammar of English-Language Computer Manuals. ACL Ezra Black, John D. Lafferty, Salim Roukos
1992	J	`jnl`	Fast Fourier Analysis for SL Exp. Math. John D. Lafferty, Daniel N. Rockmore
1992	—	`conf`	Numerical Investigation of the Spectrum for Certain Families of Cayley Graphs. Expanding Graphs John D. Lafferty, Daniel N. Rockmore
1992	—	`conf`	Towards History-based Grammars: Using Richer Models for Probabilistic Parsing. HLT Ezra Black, Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, Salim Roukos
1991	J	`jnl`	Computation of the Probability of Initial Substring Generation by Stochastic Context-Free Grammars. Comput. Linguistics Frederick Jelinek, John D. Lafferty
1990	J	`jnl`	A Statistical Approach to Machine Translation. Comput. Linguistics Peter F. Brown, John Cocke, Stephen Della Pietra, Vincent J. Della Pietra, Frederick Jelinek, John D. Lafferty, Robert L. Mercer, Paul S. Roossin