John D. Lafferty
#21,895
Most Influential Person Now
American artificial intelligence researcher
John D. Lafferty's AcademicInfluence.com Rankings
John D. Laffertycomputer-science Degrees
Computer Science
#1044
World Rank
#1082
Historical Rank
Machine Learning
#81
World Rank
#81
Historical Rank
Computational Linguistics
#252
World Rank
#256
Historical Rank
Artificial Intelligence
#306
World Rank
#311
Historical Rank
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Computer Science
John D. Lafferty's Degrees
- PhD Computer Science University of California, Berkeley
- Masters Computer Science University of California, Berkeley
- Bachelors Mathematics University of California, Berkeley
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Why Is John D. Lafferty Influential?
(Suggest an Edit or Addition)According to Wikipedia, John D. Lafferty is an American scientist, Professor at Yale University and leading researcher in machine learning. He is best known for proposing the Conditional Random Fields with Andrew McCallum and Fernando C.N. Pereira.
John D. Lafferty's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data (2001) (14270)
- Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions (2003) (3927)
- Dynamic topic models (2006) (2465)
- A Statistical Approach to Machine Translation (1990) (1986)
- A study of smoothing methods for language models applied to Ad Hoc information retrieval (2001) (1403)
- A study of smoothing methods for language models applied to information retrieval (2004) (1378)
- A correlated topic model of Science (2007) (1344)
- Inducing Features of Random Fields (1995) (1335)
- Correlated Topic Models (2005) (1101)
- Using Maximum Entropy for Text Classification (1999) (1045)
- Diffusion Kernels on Graphs and Other Discrete Input Spaces (2002) (909)
- High-dimensional Ising model selection using ℓ1-regularized logistic regression (2010) (890)
- Model-based feedback in the language modeling approach to information retrieval (2001) (859)
- Information retrieval as statistical translation (1999) (749)
- Statistical Models for Text Segmentation (1999) (713)
- The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs (2009) (659)
- Semi-supervised learning with graphs (2005) (657)
- Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions (2003) (565)
- Expectation-Propogation for the Generative Aspect Model (2002) (562)
- Mixed-membership models of scientific publications (2004) (526)
- Sparse additive models (2007) (525)
- High Dimensional Semiparametric Gaussian Copula Graphical Models (2012) (496)
- Beyond independent relevance: methods and evaluation metrics for subtopic retrieval (2003) (479)
- Conditional random fields for activity recognition (2007) (401)
- The huge Package for High-dimensional Undirected Graph Estimation in R (2012) (399)
- Language Modeling for Information Retrieval (2010) (396)
- Diffusion Kernels on Statistical Manifolds (2005) (283)
- Towards History-based Grammars: Using Richer Models for Probabilistic Parsing (1993) (282)
- Semi-supervised learning using randomized mincuts (2004) (282)
- Learning image representations from the pixel level via hierarchical sparse coding (2011) (244)
- 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 (2003) (243)
- Two-stage language models for information retrieval (2002) (242)
- A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval (2001) (242)
- Basic Methods of Probabilistic Context Free Grammars (1992) (231)
- Document language models, query models, and risk minimization for information retrieval (2001) (230)
- Probabilistic Relevance Models Based on Document and Query Generation (2003) (226)
- Time varying undirected graphs (2008) (225)
- Cranking: Combining Rankings Using Conditional Probability Models on Permutations (2002) (214)
- High-Dimensional Graphical Model Selection Using ℓ1-Regularized Logistic Regression (2006) (200)
- A Robust Parsing Algorithm for Link Grammars (1995) (200)
- Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning (2004) (199)
- Boosting and Maximum Likelihood for Exponential Models (2001) (198)
- SpAM: Sparse Additive Models (2007) (191)
- Grammatical Trigrams: A Probabilistic Model of Link Grammar (1992) (187)
- Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning (2005) (187)
- Fast nonparametric matrix factorization for large-scale collaborative filtering (2009) (178)
- Beyond Independent Relevance (2003) (177)
- A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements (2015) (176)
- Kernel conditional random fields: representation and clique selection (2004) (176)
- A risk minimization framework for information retrieval (2006) (170)
- Document Language Models, Query Models, and Risk Minimization for Information Retrieval (2001) (167)
- Computation of the Probability of Initial Substring Generation by Stochastic Context-Free Grammars (1991) (162)
- The Candide System for Machine Translation (1994) (161)
- Statistical Analysis of Semi-Supervised Regression (2007) (154)
- Semi-supervised learning : from Gaussian fields to Gaussian processes (2003) (150)
- Text Segmentation Using Exponential Models (1997) (147)
- Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent (2016) (134)
- Quadratic programming relaxations for metric labeling and Markov random field MAP estimation (2006) (129)
- Rodeo: Sparse, greedy nonparametric regression (2008) (128)
- Forest Density Estimation (2010) (121)
- Statistical Machine Translation: Final Report (1999) (117)
- Decision Tree Parsing using a Hidden Derivation Model (1994) (110)
- A Model of Lexical Attraction and Repulsion (1997) (107)
- Cyberpunc: a lightweight punctuation annotation system for speech (1998) (105)
- Visualizing Topics with Multi-Word Expressions (2009) (102)
- Person Identification in Webcam Images: An Application of Semi-Supervised Learning (2005) (100)
- CALOREE: Learning Control for Predictable Latency and Low Energy (2018) (99)
- Additive models, boosting, and inference for generalized divergences (1999) (95)
- A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints (2015) (94)
- Parallelized Variational EM for Latent Dirichlet Allocation: An Experimental Evaluation of Speed and Scalability (2007) (81)
- Time-Sensitive Dirichlet Process Mixture Models (2005) (77)
- Large-scale collaborative prediction using a nonparametric random effects model (2009) (77)
- Development and Evaluation of a Broad-Coverage Probabilistic Grammar of English-Language Computer Manuals (1992) (74)
- Sparse Nonparametric Density Estimation in High Dimensions Using the Rodeo (2007) (68)
- Decision Tree Models Applied to the Labeling of Text with Parts-of-Speech (1992) (68)
- The density manifold and configuration space quantization (1988) (66)
- Multiscale topic tomography (2007) (65)
- Union Support Recovery in Multi-task Learning (2010) (62)
- Compressed and Privacy-Sensitive Sparse Regression (2009) (62)
- Analysis, statistical transfer, and synthesis in machine translation (1992) (60)
- Fast Fourier Analysis for SL2 over a Finite Field and Related Numerical Experiments (1992) (59)
- CMU Report on TDT-2: Segmentation, Detection and Tracking (1999) (58)
- Duality and Auxiliary Functions for Bregman Distances (2001) (57)
- Sparse Nonparametric Graphical Models (2012) (56)
- Inference and Estimation of a Long-Range Trigram Model (1994) (54)
- Selective inference for group-sparse linear models (2016) (52)
- Feature selection in conditional random fields for activity recognition (2007) (52)
- ESP: A Machine Learning Approach to Predicting Application Interference (2017) (49)
- Testing Network Structure Using Relations Between Small Subgraph Probabilities (2017) (49)
- Graph Kernels by Spectral Transforms (2006) (49)
- Conditional Models on the Ranking Poset (2002) (49)
- Towards semi-supervised classification with Markov random fields (2002) (46)
- Statistical Learning Algorithms Based on Bregman Distances (1997) (46)
- Compressed Regression (2007) (44)
- Riemannian Geometry and Statistical Machine Learning (2015) (41)
- The Bigraphical Lasso (2013) (37)
- Nonparametric regression and classification with joint sparsity constraints (2008) (36)
- Cluster Expansions and Iterative Scaling for Maximum Entropy Language Models (1995) (36)
- Exponential Concentration for Mutual Information Estimation with Application to Forests (2012) (36)
- Testing for Global Network Structure Using Small Subgraph Statistics (2017) (36)
- The Nonparanormal SKEPTIC (2012) (34)
- Graph-Valued Regression (2010) (33)
- TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts (2019) (32)
- Hyperplane margin classifiers on the multinomial manifold (2004) (32)
- Adaptive risk bounds in unimodal regression (2015) (29)
- A direct geometric proof of the Lefschetz fixed point formulas (1992) (28)
- Correction: A correlated topic model of Science (2007) (28)
- TagLDA: Bringing a document structure knowledge into topic models (2006) (27)
- Cheating with imperfect transcripts (1996) (27)
- Challenges in Statistical Machine Learning (2006) (27)
- Faithful Variable Screening for High-Dimensional Convex Regression (2014) (25)
- Local Minimax Complexity of Stochastic Convex Optimization (2016) (25)
- Rodeo: Sparse Nonparametric Regression in High Dimensions (2005) (24)
- Distributed Nonparametric Regression under Communication Constraints (2018) (23)
- Sparse Additive Functional and Kernel CCA (2012) (23)
- Measure concentration of strongly mixing processes with applications (2007) (23)
- Numerical Investigation of the Spectrum for Certain Families of Cayley Graphs (1992) (23)
- Multi-strategy learning for topic detection and tracking: a joint report of CMU approaches to multilingual TDT (2002) (20)
- Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk (2001) (20)
- The Weaver System for Document Retrieval (1999) (20)
- Nonparametric Reduced Rank Regression (2012) (19)
- Surfing: Iterative optimization over incrementally trained deep networks (2019) (18)
- Information Retrieval as Statistical Translation (2017) (17)
- A derivation of the Inside-Outside algorithm from the EM algorithm (1993) (16)
- Building reliable metaclassifiers for text learning (2006) (16)
- Statistical machine learning for information retrieval (2001) (16)
- Computation-Risk Tradeoffs for Covariance-Thresholded Regression (2013) (15)
- Kernel conditional random fields : representation, clique selection, and semi-supervised learning (2004) (15)
- Word clustering with parallel spoken language corpora (1996) (15)
- Variational Chernoff Bounds for Graphical Models (2004) (14)
- Ordered Binary Decision Diagrams and Minimal Trellises (1999) (14)
- Combining Simple Discriminators for Object Discrimination (2002) (13)
- Convergence and Alignment of Gradient Descentwith Random Back propagation Weights (2021) (12)
- Spectral techniques for expander codes (1997) (12)
- Quantized Estimation of Gaussian Sequence Models in Euclidean Balls (2014) (11)
- Level Spacings for Cayley Graphs (1999) (11)
- Computationally Efficient M-Estimation of Log-Linear Structure Models (2007) (11)
- Workshop on language modeling and information retrieval (2001) (9)
- Quantized minimax estimation over Sobolev ellipsoids (2018) (9)
- Shallow neural networks trained to detect collisions recover features of visual loom-selective neurons (2021) (9)
- Topic Model (2014) (8)
- The lemur toolkit for lan-guage modeling and information retrieval (2003) (7)
- Prediction Rule Reshaping (2018) (7)
- Tree Density Estimation (2010) (7)
- Prediction and discovery : AMS-IMS-SIAM Joint Summer Research Conference, Machine and Statistical Learning: Prediction and Discovery, June 25-29, 2006, Snowbird, Utah (2007) (6)
- Eigenvalue spacings for quantized cat maps (2003) (6)
- Conditional Sparse Coding and Grouped Multivariate Regression (2012) (5)
- Sequential Nonparametric Regression (2012) (5)
- CMU Approach to TDT-2: Segmentation, Detection, and Tracking (1999) (5)
- Model Repair: Robust Recovery of Over-Parameterized Statistical Models (2020) (5)
- Prediction and Discovery (2007) (4)
- Fair quantile regression (2019) (4)
- Mismatched estimation and relative entropy in vector Gaussian channels (2013) (4)
- Techniques for exploiting unlabeled data (2008) (3)
- Modeling syntax for parsing and translation (2003) (3)
- Extraction of Protein Interaction Information from Unstructured Text Using a Link Grammar Parser (2007) (3)
- Probabilistic Decoding of Low-Density Cayley Codes (3)
- Gibbs-markov Models (1995) (3)
- Codes and Iterative Decoding on Algebraic Expander Graphs (2013) (2)
- CALOREE (2018) (2)
- Duality and Auxiliary Functions for Bregman Distances (revised) (2002) (2)
- Estimating Galaxy Spectral Functions Using Sparse Composite Models (2007) (2)
- Variational inference and learning for a unified model of syntax, semantics and morphology (2006) (2)
- Quantized Nonparametric Estimation (2015) (2)
- Denoising Flows on Trees (2016) (2)
- Comments on: Nonparametric inference with generalized likelihood ratio tests (2007) (2)
- Conditional graphical models for protein structure prediction (2006) (1)
- Spectral techniques for expander codes and generalized cyclic codes (1997) (1)
- Learning High-Dimensional Concave Utility Functions for Discrete Choice Models (2014) (1)
- Preconditioner Approximations for Probabilistic Graphical Models (2005) (1)
- Thesis Proposal Probabilistic Reasoning with Permutations: A Fourier-Theoretic Approach (2008) (1)
- Signal Decomposition using Multiscale Admixture Models (2007) (1)
- New tests of the correspondence between unitary eigenvalues and the zeros of Riemann's (2017) (1)
- Blossom Tree Graphical Models (2014) (1)
- Conditional Sparse Coding and Multiple Regression for Grouped Data (2012) (1)
- Hyperplane Margin Classifiers on the Multinomial Manifold (2004) (0)
- Clifford asymptotics and the local lefschetz index (1989) (0)
- Discriminative fields for modeling spatial dependen-cies in natural images (2001) (0)
- Optimization methods in machine learning: theory and applications (2013) (0)
- 2-2009 Sparse Additive Models (2015) (0)
- From seeing to remembering: Images with harder-to-reconstruct representations leave stronger memory traces (2023) (0)
- Acquisition of language models from text (1992) (0)
- Graph Component Analysis via Score-Matching Advisor : (2019) (0)
- Level Spacings for SL(2,p) (1997) (0)
- Level Spacings for Sl(2; P) Level Spacings for Sl 2 (f P ) (1997) (0)
- Gene family classification using a semi-supervised learning method (2007) (0)
- Dynamics of Real-world Networks (2007) (0)
- Erratum to: A Statistical Approach to Machine Translation (1991) (0)
- Informedia-II : Auto-Summarization and Visualization Over Multiple Video (2001) (0)
- on TDT-2 : Segmentation , Detection and Tracking (1999) (0)
- Algorithms : From Theory to Application (0)
- ESP : A Statistical Approach to Predicting Application Interference (2016) (0)
- Computationally and Efficient Inference for Complex Large-scale Data (2016) (0)
- Chapter 5 Multi-strategy Learning for Topic Detection and Tracking A joint report of eMU approaches to multilingual TDT (0)
- Statistical Machine Learning for Structured and High Dimensional Data (2014) (0)
- Emergent organization of receptive fields in networks of excitatory and inhibitory neurons (2022) (0)
- Approach to TDT-2 : Segmentation , Detection , and Tracking (2015) (0)
- Supplemental Material to Conditional Sparse Coding and Grouped Multivariate Regression (2013) (0)
- Sparse additive models Series B Statistical methodology (2009) (0)
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