To install click the Add extension button. That's it.

The source code for the WIKI 2 extension is being checked by specialists of the Mozilla Foundation, Google, and Apple. You could also do it yourself at any point in time.

4,5
Kelly Slayton
Congratulations on this excellent venture… what a great idea!
Alexander Grigorievskiy
I use WIKI 2 every day and almost forgot how the original Wikipedia looks like.
Live Statistics
English Articles
Improved in 24 Hours
Added in 24 Hours
What we do. Every page goes through several hundred of perfecting techniques; in live mode. Quite the same Wikipedia. Just better.
.
Leo
Newton
Brights
Milds

John D. Lafferty

From Wikipedia, the free encyclopedia

John D. Lafferty
Alma materPrinceton University (PhD, MA)
Middlebury College (BA)
Known forConditional Random Fields
AwardsIEEE Fellow (2007)[1]
Test-of-Time Award of ICML (2011,2012)[2][3]
Classic paper prizes of ICML (2013)[4]
Test of Time Award of SIGIR (2014)[5]
Scientific career
FieldsComputer Science
Machine Learning
InstitutionsYale University
University of Chicago
Carnegie Mellon University
IBM Research
Harvard University
Doctoral studentsChengXiang Zhai
Other notable studentsDavid Blei (Post Dr.)
Websiteseas.yale.edu/faculty-research/faculty-directory/john-lafferty

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.[4]

YouTube Encyclopedic

  • 1/3
    Views:
    18 600
    17 464
    1 529 924
  • Modeling Science: Dynamic Topic Models of Scholarly Research
  • The Alignment Problem: Machine Learning and Human Values with Brian Christian
  • Luis Elizondo: Gov't Has Biological UFO Samples [Part 2]

Transcription

Biography

In 2017, Lafferty was appointed the John C. Malone Professor of Statistics and Data Science at Yale University.[6] He previously taught at the University of Chicago as Louis Block Professor of Statistics and Computer Science,[6] and has held positions at the University of California, Berkeley and the University of California, San Diego. His research interests lie in statistical machine learning,[2][3] information retrieval,[5] and natural language processing,[7] with a focus on computational and statistical aspects of nonparametric methods, high-dimensional data and graphical models.

Prior to University of Chicago in 2011, he was faculty at Carnegie Mellon University since 1994, where he helped to found the world's first machine-learning department. Before CMU, he was a Research Staff Member at IBM Thomas J. Watson Research Center, where he worked on natural speech and text processing in the group led by Frederick Jelinek. Lafferty received a Ph.D. in Mathematics from Princeton University, where he was a member of the Program in Applied and Computational Mathematics, under Edward Nelson in 1986. He was an assistant professor in the Mathematics Department at Harvard University before joining IBM.[8]

He was elected Fellow of IEEE in 2007 "for contributions to statistical pattern recognition and statistical language processing".[1]

Academic career

Lafferty has held many prestigious positions, including: 1) program co-chair and general co-chair of the Neural Information Processing Systems (NIPS) Foundation conferences; 2) co-director of CMU's new Ph.D. Machine Learning Ph.D. Program; 3) associate editor of the Journal of Machine Learning Research[9] and the Electronic Journal of Statistics; and 4) member of the Committee on Applied and Theoretical Statistics (CATS) of the National Research Council.[10]

He has also received numerous awards, including two Test-of-Time awards at the International Conference on Machine Learning (ICML) 2011 & 2012,[2][3] classic paper prize of ICML 2013,[4] and Test-of-Time awards at the Special Interest Group on Information Retrieval (SIGIR) 2014.[5]

Selected works

  • 1990. A statistical approach to machine translation.[7]
The idea of statistical machine translation was born in the labs of IBM Research.[11]
  • 2001. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data.
Test-of-Time Award of ICML 2011.[2]
  • 2002. Diffusion Kernels on Graphs and Other Discrete Input Spaces.
Test-of-Time Award of ICML 2012.[3]
  • 2003. Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions.
Classic paper prizes of ICML 2013.[4]
  • 2003. Beyond independent relevance: methods and evaluation metrics for subtopic retrieval.
Test of Time Award of SIGIR 2014.[5]
  • 2006. Dynamic topic models. ICML'06.

See also

References

  1. ^ a b "John Lafferty (IEEE Fellow in 2007)". IEEE. IEEE. 2007. Retrieved 15 December 2014.
  2. ^ a b c d "Test-of-Time Award ICML'11". ICML. 2011. Retrieved 15 December 2014.
  3. ^ a b c d "Test-of-Time Award ICML'12". ICML. 2012. Retrieved 15 December 2014.
  4. ^ a b c d "Two classic paper prizes for papers that appeared at ICML 2013". ICML. 2013. Retrieved 15 December 2014.
  5. ^ a b c d "SIGIR 2014 Best Paper Awards". SIGIR. 2014. Retrieved 15 December 2014.
  6. ^ a b "John Lafferty appointed the Malone Professor of Statistics and Data Science". Yale University. November 2, 2017. Retrieved October 10, 2021.
  7. ^ a b Peter F. Brown; John Cocke (June 1990). "A statistical approach to machine translation". Computational Linguistics. MIT Press. 16 (2): 79–85. Retrieved 14 December 2014.
  8. ^ "John Lafferty bio (ICMLA'06)" (PDF). ICMLA. 2006. Retrieved 15 December 2014.
  9. ^ "JMLR Editorial Board". JMLR. Retrieved 15 December 2014.
  10. ^ "Member Biographies (CATS)". Committee on Applied and Theoretical Statistics (CATS). National Research Council. Retrieved 15 December 2014.
  11. ^ Philipp Koehn (2009). Statistical Machine Translation. Cambridge University Press. p. 17. ISBN 978-0521874151. Retrieved 22 March 2015. In the late 1980s, the idea of statistical machine translation was born in the labs of IBM Research.

External links

This page was last edited on 27 February 2024, at 02:17
Basis of this page is in Wikipedia. Text is available under the CC BY-SA 3.0 Unported License. Non-text media are available under their specified licenses. Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc. WIKI 2 is an independent company and has no affiliation with Wikimedia Foundation.