NLP Reading Group

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The reading group attempts to keep abreast of current trends in natural language processing research. We typically read one or two recent NLP conference papers each week, and occasionally look at material from the machine learning, statistics, and linguistics communities as well.

Starting in 2008, we will be posting the weekly readings here. Past readings since 2001 are being filled in presently.

Spring 2008

First meeting of the term will be on Thursday, Jan. 31, at noon in NEB 317. Feel free to bring lunch.

Fall 2007

Topics:

  • Domain adaptation
  • Recent parsing work
  • Text compression
  • Semisupervised learning


Date/Time Presenter Paper(s) Supporting Papers/Notes
Sep.26 Omar F Zaidan J. Blitzer, R. McDonald, F. Pereira

Domain Adaptation with Structural Correspondence Learning

EMNLP 2006

Oct.3 David Smith Shai Ben-David, John Blitzer, Koby Crammer, Fernando Pereira.

Analysis of Representations for Domain Adaptation.

Oct. 10 Nathaniel W Filardo Mahoney, Matthew

Adaptive Weighing of Context Models for Lossless Data Compression.

Florida Institue of Technology, CS Department, Technical report CS-2005-16

EMNLP-CoNLL 2007

Oct. 17 Markus Dreyer Nakagawa, Tetsuji

Multilingual Dependency Parsing Using Global Features

EMNLP-CoNLL 2007

Oct. 26 Christo Kirov Seginer, Yoav

Fast Unsupervised Incremental Parsing (syntax induction)

Proceedings ACL 2007


Nov. 3 Christo Kirov I. Titov, J. Henderson

Constituent Parsing with Incremental Sigmoid Belief Networks

ACL 2007

Nov. 17 David Smith X. Zhu

Semi-Supervised Learning Literature Survey

Dec. 12 Delip Rao M. Belkin, P. Niyogi

Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

ACM 2002


Mikhail Belkin, Partha Niyogi, Vikas Sindhwani

On Manifold Regularization

Summer 2007

Topics:

  • Good recent papers (mainly from 2007)


Date/Time Presenter Paper(s) Supporting Papers/Notes
May 10 David Smith M. Johnson, T. Griffiths, and S. Goldwater

Bayesian Inference for PCFGs via Markov Chain Monte Carlo

HLT/NAACL 2007

May 17 Markus Dreyer M. Galley, K. McKeown

Lexicalized Markov Grammars for Sentence Compression

HLT/NAACL 2007


June 2 Erin Fitzgerald J. Jiang, C. Zhai

A Systematic Exploration of the Feature Space for Relation Extraction

HLT/NAACL 2007

June 6 Nikesh Garera A. Alexandrescu, K. Kirchhoff

Data-Driven Graph Construction for Semi-Supervised Graph-Based Learning in NLP

HLT/NAACL 2007

June 14 David Smith X. Zhu, Z. Ghahramani,J. Lafferty

Semi-supervised learning using Gaussian fields and harmonic functions.

ICML 2003

June 21 Christopher White K. Murphy, Y. Weiss, M. Jordan

Propagation for approximate inference: An empirical study.

15th UAI, pages 467-?75, 1999

... discussing (loopy) belief propagation as background for survey propagation, a topic which has been getting more attention lately for its ability to "solve very large hard combinatorial problems, such as determining the satisfiability of Boolean formulas.

Chapter 8 of Chris Bishop's textbook is supposed to be a good treatment of graphical models overall. It is available free here [1]. He covers BP in section 8.4.4 after first presenting factor graphs in 8.4.3.

David MacKay's treatment of BP, also in terms of factor graphs, is in chapter 26 of his book [2]. It's worth reading this chapter in full, perhaps first reading chapter 16. ... the update equations are given as (26.11) and (26.12) ... [substantial further discussion by jason was here]

Some people may prefer Bishop's style, others MacKay's.

July 6 Christopher White A. Braunstein, M. Mezard, R. Zecchina.

Survey propagation: an algorithm for satisfiability.

Random Structures and Algorithms, 2005.

We sent some questions to Zecchina.

Lukas Kroc, Ashish Sabharwal and Bart Selman.

Survey Propagation Revisited: An Empirical Study.

23rd UAI, 2007.

July 18 David Smith P. Liang, S. Petrov, M. Jordan, D. Klein

The Infinite PCFG Using Hierarchical Dirichlet Processes.

Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning,

Aug. 3 Yi Su M. Galley, K. McKeown

Lexicalized Markov Grammars for Sentence Compression.

NAACL-HLT 2007

Aug. 11 Nikesh Garera L. Shen, G. Satta, A. Joshi.

Guided learning for bidirectional sequence classification

ACL 2007

Aug. 18 Markus Dreyer D. Talbot, M. Osborne

Randomised Language Modelling for Statistical Machine Translation

ACL 2007

They use a space-efficient randomized data structure (Bloom Filter) to store very large n-gram models.

There is a companion paper that people might want to have a quick look at as well, for comparison:

D. Talbot, M. Osborne

Smoothed Bloom Filter Language Models: Tera-Scale LMs on the Cheap

ACL 2007

Aug. 30 Delip Rao Gideon S. Mann

Simple, Robust, Scalable Semi-supervised Learning via Expectation Regularization

Proceedings of the 24 th International Conference on Machine Learning 2007


Spring 2007

Topics:

  • Morphology (unsupervised learning)
  • Recent IR/QA papers (with an NLP or multilingual focus)
  • Integrating search and learning


Date/Time Presenter Paper(s) Supporting Papers/Notes
Apr. 19 John Blatz A. Prieditis

Machine discovery of Effective Admissible Heuristics

Machine Learning Journal, 1993

Apr. 12 Markus Dreyer A. Haghighi, J. DeNero and D. Klein

Approximate Factoring for A* Search

NAACL-HLT 2007

Mar. 29 & Apr. 5 Zhifei Li H. Daume III, J. Langford, and D. Marcu

Search-based structured prediction.

Machine Learning Journal, forthcoming

Mar. 8 David Smith H. Daume III & D. Marcu

Learning as search optimization: approximate large margin methods for structured prediction.

ICML 2005

Mar. 1 Wei Chen M. Kaisser, S. Scheible, and B. Webber

Experiments at the University of Edinburgh for the TREC 2006 QA track.

TREC-15

They do some fairly deep interpretation of sentences, extracting their predicate-argument structure.
Feb. 22 Eric Harley K. Kan Lo & W. Lam

Using Semantic Relations with World Knowledge for Question Answering

TREC-15

Feb. 15 Nikhil Bojja C. Monson et. al.

Unsupervised Induction of Natural Language Morphology Inflection Classes

ACL Student Workshop '04

Feb. 8 Delip Rao P. Schone and D. Jurafsky

Knowledge-free induction of morphology using latent semantic analysis

CoNLL 2000

However, there was an extension of this work reported in NAACL-2001 that looks at circumfixes and prefix/affix combinations. [3]


Feb. 1 Nikesh Garera D. Yarowsky and R. Wicentowski

Minimally supervised morphological analysis by multimodal alignment

ACL 2000

For more details refer to Chapter 4 of Wicentowski's thesis.

Fall 2006

Topics:

  • Machine learning: Margin methods and structured classification
  • Linguistics: Syntactic formalisms
  • Syntax-based MT


Date/Time Presenter Paper(s) Supporting Papers/Notes
Dec. 13 Delip Rao J. Carbonell et. al.

Context-based machine translation

AMTA 2006

Dec. 6 Jason Smith M. Galley et. al.

Scalable Inference and Training of Context-Rich Syntactic Translation Models

ACL 2006

It may also be helpful to look at:

M. Galley et. al.

What's in a translation rule?

HLT/NAACL 2004


Nov. 29 Balakrishnan V D. Marcu et. al.

SPMT: Statistical Machine Translation with Syntactified Target Language Phrases

EMNLP 2006

Nov. 15 Eric Harley D. Chiang

An introduction to synchronous grammars

ACL 2006 Tutorial

Slides from the talk are also available. [4]
Nov. 8 Elliott Drabek K.Shklovsky

A Grammatical Sketch of Petalcingo Tzeltal

Undergraduate Thesis, Reed College, 2005

It is 77 pages long, but not dense, and I will be skipping the following sections:

Pages

01-14 Phonetics and phonology

18-18 Polyvalence

21-21 Inherent possession and ...

46-55 Tense and aspect and other sections

Nov. 1 Yi Su M. Steedman

Gapping as Constituent Coordination

Linguistics and Philosophy, Vol. 13, 1990, pp.207-264.

See Yi for photocopies.
Oct. 25 Markus Dreyer S. Reizler et. al.

Parsing the Wall Street Journal using a Lexical-Functional Grammar and Discriminative Estimation Techniques

ACL 2002


Oct. 18 Erin Fitzgerald J. Bresnan & R.M. Kaplan

Lexical-Functional Grammar: A Formal System for Grammatical Representation

The Mental Representation of Grammatical Relations, MIT Press, 1982

BTW, the edited collection that this appears in is generally interesting. Bresnan defends and develops lexicalized grammars in general; the idea of separate surface and semantic roles; and Bresnan & Kaplan's LFG in particular. You should know that she originated (in 1978) the extremely influential idea of lexicalized syntax -- the idea that a grammar is simply a collection of lexical entries to be assembled in standard language-independent ways, but that there are also "lexical redundancy rules" that relate, e.g., active and passive entries for the same verb. Some chapters address morphological and cognitive issues pertaining to lexicalization, including an essay by Pinker on lexicalist learning.

Slides from Erin's presentation can be found here.

Oct. 11 John Blatz L.Xu, D. Wilkinson, F. Southey, & D. Schuurmans

Discriminative Unsupervised Learning of Structured Predictors

ICML 2006

Oct. 4 Nikesh Garera A. Culotta & J. Sorensen

Dependency Tree Kernels for Relation Extraction

ACL 2004


D. Zelenko, C. Aone, & A. Richardella

Kernel Methods for Relation Extraction

JMLR, Volume 3, 2003

Sept. 27 David Smith C. Cortes, P. Haffner, & M. Mohri

Rational Kernels

NIPS 2003

Papers extending rational kernels, including results on positive semidefinite cases, are at:[5]

For the record, and not to be read, is an interesting parallel line of research in Fisher Kernels over strings, e.g. this paper by Saunders, Shawe-Taylor and Vinokourov: [6]

Sept. 20 Elliot Drabek K.Q. Weinberger, F. Sha, & L.K. Saul

Learning a kernel matrix for nonlinear dimensionality reduction

ICML 2004

S.T. Roweis & L.K. Saul

Nonlinear Dimensionality Reduction by Locally Linear Embedding

Science, 22 December 2000


J.B. Tenenbaum, V. De Silva, & J.C. Langford

A global geometric framework for nonlinear dimensionality reduction

Science, 22 December 2000

Sept. 13 Roy Tromble L. Xu, J. Neufeld, B. Larson, & D. Schuurmans

Maximum Margin Clustering

NIPS 2004

Summer 2006

Spring 2006

Fall 2005

Date/Time Presenter Paper(s) Supporting Papers/Notes
Sept. 14 Nikesh Garera M. Jordan

Statistical Learning Theory Chapter 8 (Exponential family and Generalized linear models)

Sept. 21 Arnab Ghoshal M. Jordan

Statistical Learning Theory Chapter 2&3

Oct. 20 Roy Tromble Sheila M. Reynolds, Jeff A. Bilmes

Part-of-Speech Tagging using Virtual Evidence and Negative Training.

Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing. 2005. pp 459--466.

Oct. 27 Markus Dreyer D. Roth and W. Yih

Integer Linear Programming Inference for Conditional Random Fields.

ICML '2005


Nov. 4 Jason Riesa Luke S. Zettlemoyer, Michael Collins.

Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial

Proceedings of UAI 2005

Nov. 16 Safiullah Shareef Hassan Sawaf, Jörg Zaplo, Hermann Ney

Statistical Classification Methods for Arabic News Articles

Nov. 23 Roy Tromble Sutton, Charles and McCallum, Andrew

Composition of Conditional Random Fields for Transfer Learning

Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing 2005

Summer 2005

Topics:

  • Recent papers on ACL / CoNLL / parallel-text workshop
  • Optimality Theory
  • Unsupervised/semisupervised/EM
  • AI
  • Graphical Models
  • Dependency Parsing
  • Kernels
  • Algorithms
  • Syntactic MT
  • MT Techniques
  • Non-dependency parsing
Date/Time Presenter Paper(s) Supporting Papers/Notes
July 14 Roy Tromble Goldwater and Johnson

[http://www.cog.brown.edu:16080/~sgwater/papers/OTvar03.pdf Learning OT Constraint Rankings Using a Maximum

Entropy Model]

In Proceedings of the Workshop on Variation within Optimality Theory, 2003


July 21 Keith and Damianos Sharon Goldwater, Mark Johnson

[http://www.aclweb.org/anthology/W/W05/W05-0615 Representational Bias in Unsupervised Learning of Syllable

Structure]

ACL 2005


Ando, Rie and Zhang, Tong

[http://www.aclweb.org/anthology/P/P05/P05-1001 A High-Performance Semi-Supervised Learning Method for Text

Chunking]

ACL 2005


July 28 Zak Takuya Matsuzaki, Yusuke Miyao, Jun'ichi Tsujii

Probabilistic CFG with Latent Annotations

ACL 2005

Aug 5 Adam Duh, Kevin and Kirchhoff, Katrin

[http://www.aclweb.org/anthology/W/W05/W05-0708 Tagging of Dialectal Arabic: A Minimally Supervised

Approach]

ACL 2005


Aug 19 John Blatz Niyogi, Sourabh

Steps Toward Deep Lexical Acquisition

ACL 2005

Aug 26 Roy Tromble Jenny Rose Finkel, Trond Grenager, Christopher Manning

[http://www.aclweb.org/anthology/W/W05/W05-0511 Incorporating Non-local Information into Information

Extraction Systems by Gibbs Sampling]

ACL 2005

Sep.1 Markus Nikesh, John Blatz B. Walsh

[http://nitro.biosci.arizona.edu/courses/EEB581-2004/handouts/Gibbs.pdf Markov Chain Monte Carlo and Gibbs Sampling]

Lecture Notes for EEB 581, version 26 April 2004


Spring 2005

Topics:

  • Bayesian nets / inference (tutorials in Michael Jordan's book)
  • Dependency Networks
Date/Time Presenter Paper(s) Supporting Papers/Notes
Feb. 25 David Smith M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul

Learning in Graphical Models

MIT Press, 1999

Mar. 4 David Smith M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul

Learning in Graphical Models

MIT Press, 1999

Mar. 11 David Smith M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul

Learning in Graphical Models

MIT Press, 1999

Apr. 2 David Smith M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul

Learning in Graphical Models

MIT Press, 1999

Apr. 9 Noah A Smith G. Elidan and N. Friedman.

The Information Bottleneck EM Algorithm

UAI 2003


Gal Elidan, Nir Friedman

Learning Hidden Variable Networks

JMLR 2005

Apr. 16 Noah A Smith V. Lavrenko, S.L Feng, R. Manmatha

Statistical models for automatic video annotation and retrieval

Acoustics, Speech, and Signal Processing, 2004. Proceedings.

Apr. 21 Omar F. Zaidan Tin Kam Ho, Jonathan J. Hull, Sargur N. Stihari

Decision Combination in Multiple Classifier Systems

IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.16. No I. Jan. 1994


Dan Klein, Kristina Toutanova, H. Tolga Ilhan, Sepandar D. Kamvar and Christopher D. Manning

Combining Heterogeneous Classifiers forWord-Sense Disambiguation

ACL 2002

Apr. 28 Damianos Karakos Alessandro Moschitti and Roberto Basili

Complex Linguistic Features for Text Classification: a comprehensive study

In proceedings of the 26th European Conference on Information Retrieval Research (ECIR 2004)

May 7 Markus Dreyer M. Diligenti, F.M. Coetzee, S. Lawrence, C.L. Giles, M. Gori

Focused Crawling Using Context Graphs

26th International Conference on Very Large Databases, VLDB 2000


Adam Kilgarriff and Gregory Grefenstette

Introduction to the Special Issue on the Web as Corpus

Computational Lingustics, 2003


Fall 2004

Topics:

  • Recent papers from ACL/EMNLP 2004
  • Graph methods
  • Unification parsing
  • Parsing strategies
  • Syntax for MT or vice-versa
  • TAG-based noisy channel model of speech repairs
  • Collective information extraction with relational Markov networks
Date/Time Presenter Paper(s) Supporting Papers/Notes
Aug. 20 Damianos Karakos, Charles Schafer P. Pantel and D. Lin

Discovering word senses from text

Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, 2002


Diana McCarthy, Rob Koeling, Julie Weeds, John Carroll

[ftp://ftp.informatics.susx.ac.uk/pub/users/dianam/senseranks.pdf Finding Predominant Word Senses in

Untagged Text]

2004

Aug. 27 David Smith I. Dan Melamed

Statistical Machine Translation by Parsing

ACL 2004


Daniel Gildea

[http://acl.ldc.upenn.edu/acl2004/emnlp/pdf/Gildea.pdf Dependencies vs. Constituents for Tree-Based

Alignment]

ACL 2004

Sep. 2 Gideon Mann Xin Li, Paul Morie, and Dan Roth

[http://acl.ldc.upenn.edu/hlt-naacl2004/main/pdf/139_Paper.pdf Robust Reading: Identification and Tracing

of Ambiguous Names]

ACL 2004


Cheng Niu, Wei Li, Rohini K. Srihari

[http://acl.ldc.upenn.edu/acl2004/main/pdf/372_pdf_2-col.pdf Weakly Supervised Learning for Cross-Document

Person-Name Disambiguation Supported by Information Extraction]

ACL 2004

Sep. 9 John Blatz Pascale Fung and Percy Cheung

[http://acl.ldc.upenn.edu/acl2004/emnlp/pdf/Fung.pdf Mining Very-Non-Parallel Corpora: Parallel Sentence

and Lexicon Extraction via Bootstrapping and EM]

ACL 2004


Dragos Stefan Munteanu, Alexander Fraser and Daniel Marcu

[http://acl.ldc.upenn.edu/hlt-naacl2004/main/pdf/93_Paper.pdf Improved Machine Translation Performance via

Parallel Sentence Extraction from Comparable Corpora]

ACL 2004

Sep. 24 Roy Tromble B. Taskar, C. Guestrin and D. Koller

Max-Margin Markov Networks

Neural Information Processing Systems Conference (NIPS03), 2003


B. Taskar, D. Klein, M. Collins, D. Koller and C. Manning

Max-Margin Parsing

EMNLP 2004



Oct. 2 Nguyen Bach Background knowledge on SVM and Graphical Models

Intro SVM

Intro Graphical Models


Oct. 15 Nguyen Bach Daichi Mochihashi, Genichiro Kikui, Kenji Kita

[http://acl.ldc.upenn.edu/acl2004/emnlp/pdf/Mochihashi.pdf Learning Nonstructural Distance Metric by

Minimum Cluster Distortions]

EMNLP 2004

Oct. 22 Michelle Vanni Lin and Och

[http://acl.ldc.upenn.edu/acl2004/main/pdf/215_pdf_2-col.pdf Automatic Evaluation of Machine Translation

Quality Using Longest Common Subsequence]

ACL 2004


Babych and Hartley

[http://acl.ldc.upenn.edu/acl2004/main/pdf/349_pdf_2-col.pdf Extending the BLEU MT Evaluation Method with

Frequency Weightings]

ACL 2004

Oct. 29 Eric Goldlust Clark and Curran

[http://web.comlab.ox.ac.uk/oucl/work/stephen.clark/papers/acl04.pdf Parsing the WSJ using CCG and Log-

Linear Models]

ACL 2004

Nov. 5 Michelle Vanni Robert S. Swier and Suzanne Stevenson

Unsupervised Semantic Role Labelling

EMNLP 2004


Nianwen Xue, Martha Palmer

Calibrating Features for Semantic Role Labelling

EMNLP 2004

Nov. 13 Michelle Vanni Robert S. Swier and Suzanne Stevenson

[nlp.cs.jhu.edu/~cschafer/david/Ch2.pdf Inexact Graph Matching Using Estimation of Distribution

Algorithms,Chapter 2, The graph matching problem]

Submitted to the Ecole Nationale Supérieure des Télécommunications (Paris), for the Degree of Doctor of

Philosophy. 2002


Yakov Keselman, Ali Shokoufandeh, M. Fatih Demirci, Sven Dickinson

[nlp.cs.jhu.edu/~cschafer/david/many-to-many-graph.pdf Many-to-Many Graph Matching via Metric Embedding]

Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE

...This chapter is general to the field although pretty sweeping and unspecific as a result. It probably makes a

good introduction, since it gives an idea of the scope and diversity of the problem and proposed techniques...

...this is a state of the art paper which is quite dense but quite interesting. solves a very general formulation

of inexact graph matching by first imbedding graphs into a normed space...


Nov. 20 David Smith Olle H鋑gstr鰉 and Karin Nelander

On Exact Simulation of Markov Random Fields Using Coupling from the Past

Foundation of the Scandinavian Journal of Statistics, 1999


James Fill and Mark Huber

The Randomness Recycler: A New Technique for erfect Sampling.

IEEE Symposium on Foundations of Computer Science, 2000


Nov. 27 Jia Cui David M. Blei, Andrew Y. Ng, Michael I. Jordan

Latent Dirichlet Allocation

Journal of machine Learning Research 3, 2003

A additional related report on LDA

[www.cs.toronto.edu/~ywteh/research/npbayes/report.pdf]

Another introduction to LDA

[7]


Spring 2004

Topics:

  • combinatorial optimization (software)
  • optimality theory
  • information extraction
Date/Time Presenter Paper(s) Supporting Papers/Notes
Feb. 5 Brock Jessica A. Barlow and Judith A. Gierut

Optimality theory in phonological acquisition

Journal of Speech, Language and Hearing 42, 1999

----

Paul Boersma, Joost Dekkers and Jeroen van de Weijer

Introduction. In Optimality Theory: Phonology, Syntax and Acquisition

Oxford University Press 2000

Feb. 12 Brock Bob Frank, Giorgio Satta

Optimality theory and the Generative Complexity of Constraint Violability

MIT Press

A glimpse (from MIT Press):

It has been argued that rule-based phonological descriptions can uniformly be expressed as mappings carried out by finite-state transducers, and therefore fall within the class of rational relations. If this property of generative capacity is an empirically correct characterization of phonological mappings, it should hold of any sufficiently restrictive theory of phonology, whether it utilizes constraints or rewrite rules. In this paper, we investigate the conditions under which the phonological descriptions that are possible within the view of constraint interaction embodied in Optimality Theory (Prince and Smolensky 1993) remain within the class of rational relations. We show that this is true when GEN is itself a rational relation, and each of the constraints distinguishes among finitely many regular sets of candidates.

Feb. 19 David Smith Barzilay and Lee

Learning to Paraphrase: An Unsupervise Approach Using Multiple-Sequen7:12 PM 2/4/2008ce Alignment

HTL 2003

Mar. 5 Charles Schafer Daniel Marcu

Theory and Practice of Discourse Parsing and Summarization, Chapters 2 & 3

The MIT Press, 2000

Mar. 18 Markus Dreyer Eugene Charniak, Niyu Ge, John Hale

A Statistical Approach to Anaphora Resolution

Proceedings of the Sixth Workshop on Very Large Corpora, 1998

Mar. 25 Eric Goldlust Boyan and Moore

Learning Evaluation Functions to Improve Optimization by Local Search

Journal of Machine Learning Research, 2000

Apr. 3 Roy Tromble Roman Bartak

Constraint Programming: In Pursuit of the Holy Grail

1999

Apr. 10 Noah Ashton Smith Denys Duchier

Axiomatizing Dependency Parsing Using Set Constraints

Sixth Meeting on Mathematics of Language, 2000

Apr. 10 Noah Ashton Smith Denys Duchier

Axiomatizing Dependency Parsing Using Set Constraints

Sixth Meeting on Mathematics of Language, 2000

Apr. 17 Elliott Franco Drabek Rina Dechter

Mini-Buckets: A General Scheme for Generating Approximations in Automated Reasoning

2001

Apr. 24 David Smith McCallum and Jensen

Extraction and Data Mining using Conditional-Probability, Relational Models

IJCAI'03 Workshop on Learning Statistical Models from Relational Data, 2003

The paper is a survey of recent trends in IE and data mining (biased of course towards the authors' work) and a proposal to unify them with conditional random fields.
May. 1 Izhak Shafran Eric J. Friedman

Strong Monotonicity in Surplus Sharing

1999

Used Tom Dietterich has a web page on probabilistic relational models:

[8]

May. 15 Roy Tromble Fuchun Peng, Andrew McCallum

Accurate Information Extraction from Research Papers using Conditional Random Fields

2004

Fall 2003

Date/Time Presenter Paper(s) Supporting Papers/Notes
Sep.11 Elliott Franco Drabek Bernard Comrie

Language Universals Linguistic Typology: Syntax and Morphology Language Universals Linguistic Typology:

Syntax and Morphology, Chapter 1

Blackwell Pub (1989)

Sep.18 David Smith Bernard Comrie

Language Universals Linguistic Typology: Syntax and Morphology Language Universals Linguistic Typology:

Syntax and Morphology, Chapter 2-3

Blackwell Pub (1989)

Oct. 3 Michelle Vanni Bernard Comrie

Language Universals Linguistic Typology: Syntax and Morphology Language Universals Linguistic Typology:

Syntax and Morphology, Chapter 4-6

Blackwell Pub (1989)

Oct. 10 David Smith Bernard Comrie

Language Universals Linguistic Typology: Syntax and Morphology Language Universals Linguistic Typology:

Syntax and Morphology, Chapter 6-7

Blackwell Pub (1989)

Oct. 24 Markus Dreyer Stuart M. Shieber, Yves Schabes

Synchronous Tree-Adjoining Grammars

Coling 1990

An additional closely related paper

Stuart M. Shieber, Yves Schabes


Generation and Synchronous Tree-Adjoining Grammars

Fifth International Workshop on Natural Language Generation.

Oct. 31 Roy Tromble Dekai Wu

An algorithm for simultaneously bracketing parallel texts by aligning words

ACL 1995

Nov. 6 Brock Pytlik Stuart M. Shieber

Transducers as a Substrate for Natural Language Processing

Nov. 13 Markus Dreyer Goldman and Zhou

Enhancing Supervised Learning with Unlabeled Data

27th Int. Conf. on Mach. Learn. 2000

An additional paper with some experiments

Clark, Curran and Osborne

Bootstrapping POS taggers using Unlabelled Data

CoNLL 2003

Nov. 20 Noah A. Smith Rebecca Hwa, Miles Osborne, Anoop Sarkar, Mark Steedman

Corrected Co-training for Statistical Parsers

ICML 2003

Dec. 12 Paola Virga Kamal Nigam and Rayid Ghani

Analyzing the Effectiveness and Applicability of Co-training

Ninth International Conference on Information and Knowledge Management 2000

Spring 2003

Date/Time Presenter Paper(s) Supporting Papers/Notes
Feb. 13 David Smith K. Church

Empirical Estimates of Adaptation: The chance of Two Noriega's is closer to p/2 than p^2

Coling 2000, pp. 173-179


Feb. 19 Elliott Drabek A. Lopez􀀀, M. Nossal􀀀, R. Hwa, P. Resnik

Word-level Alignment for Multilingual Resource Acquisition

Proceedings of the 2002 LREC Workshop on Linguistic Knowledge Acquisition and Representation: Bootstrapping Annotated Language Data


Feb. 26 Elliott Drabek Steven Abney

Bootstrapping

ACL'02

Mar.6 Paola Virga Carl M. Kadie, Christopher Meek, David Heckerman

A Collaborative Filtering System Using Posteriors Over Weights of Evidence

Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence, 2002.


Mar.20 Roy Tromble Nikita Schmid, Ahmed Patel

[ttp://arXiv.org/abs/cs/0201008 Using Tree Automata and Regular Expressions to Manipulate Hierarchically Structured Data]

Apr.10 V. N. Vapnik

The Nature of Statistical Learning Theory, Intro and Chapters 1, 2A

Apr.17 Roy Tromble V. N. Vapnik

The Nature of Statistical Learning Theory,Chapters 2B - 4A

Apr. 24 Paola V. N. Vapnik

The Nature of Statistical Learning Theory, Chapters 4B - 5A

May 1 Noah V. N. Vapnik

The Nature of Statistical Learning Theory, Chapters 5B - 6A

May 8 Noah V. N. Vapnik

The Nature of Statistical Learning Theory, Chapters 6B - 7A

May 15 Chal V. N. Vapnik

The Nature of Statistical Learning Theory, Chapters 7B -

Fall 2002

Date/Time Presenter Paper(s) Supporting Papers/Notes
Sep. 10 Noah A. Smith Collins, Duffy.

New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron.

ACL '2002

Sep. 19 Paola Virga Yamada, Knight

A decoder for Syntax-based Statistical MT

ACL '2002

Sep. 26 Paul Ruhlen Hwa, Resnik, Weinberg, Kolak

Evaluating Translational Correspondence using Annotation Projection

ACL '2002

Oct. 2 Gideon Mann Gildea, Jurafsky

Automatic Labeling of Semantics Roles

ACL '2001

Oct. 8 Elliott Franco Drabek Ravichandran, Hovy

Learning Surface Text Patterns for a Question Answering System.

ACL '2001

A similar paper

Lin, Pantel

Discovery of Inference Rules for Question Answwering

Oct. 17 David Smith Cotton, Bird

An Integrated Framework for Treebanks and Multilayer Annotations

LREC '2002

Oct. 24 Roy Tromble Han, Benjamin

Building a Bilingual Dictionary with Scarce Resources: A Genetic Algorithm Approach.

Nov. 1 Chalaporn Hathaidharm J.Gao, J.Goodman, M.Li, K.Lee

Toward A Unified Approach To Statistical Language Modeling For Chinese

ACM Transactions on Asian Language Information Processing, Vol. 1, No. 1, pp 3-33. 2002.

Nov. 7 Neda Khalili Yamamoto, Church

Using Suffix Arrays to Compute Term Frequency and Document Frequency for All Substrings in a Corpus

Computational Linguistics '2001

A relative paper:

Kageura

Bigram Statistics Revisited A Comparative Examination of Some Statistical Measures in Morphological Analysis of Japanese Kanji Sequences

Nov. 14 Michelle Vanni Hearst

Untangling Text Data Mining.

ACL '1999

Nov. 21 Silviu Cucerzan Ueda, Nakano, Ghahramani, Hinton

SMEM Algorithm for Mixture Models

Neural Information Processing Systems '1998

Dec.5 Silviu Cucerzan Pearce

A Comparative Evaluation of Collocation Extraction Techniques. Darren Pearce.

Third International Conference on Language Resources and Evaluation. May. 2002


D. Lin

Automatic identification of non-compositional phrases.

In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, 317--324.


Summer 2002

Date/Time Presenter Paper(s) Supporting Papers/Notes
July. 24 Michelle Vanni Merlo

A Multilingual Paradigm for Automatic Verb Classification

ACL '2002

July. 31 Paola Virga Yamada, Knight

A decoder for Syntax-based Statistical MT

ACL '2002

Spring 2002

Date/Time Presenter Paper(s) Supporting Papers/Notes
Feb. 7 Paola Virga Knight, Graehl

Machine Transliteration

Proceedings of the Thirty-Fifth Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics

Feb. 14 Charles Schafer Yaser, Germann

Translating with Scarce Resources

American Association for Arti�cial Intelligence 2000

Feb. 21 Jia Cui Barzilay, McKeown

Extracting Paraphrases from a Parallel Corpus

Computer Science Department Columbia.Univ.

Feb. 28 Silviu Cucerzan Marcu

Towards a Unified Approach to Memory- and Statistical-Based Machine Translation.

Annual Meeting of the ACL, Proceedings of the 39th Annual Meeting on Association for Computational Linguistics '2001

Mar. 14 Noah A. Smith Ratnaparkhi

A Simple Introduction to Maximum Entropy Models for NLP

Institute for Research in Cognitive Science, Univ. of Penn.

Mar. 28 Swapna Somasundaran Crestan, El-Beze

Improving supervised WSD by including rough semantic features in a Multilevel view of the Context

SEMPRO Workshop, Edinburgh, 2001.

Apr. 11 Paola Virga Neal, Hinton

A view of the EM algorithm that justifies incremental, sparse, and other variants

Learning in Graphical Models, 1999

Apr. 18 Paul Ruhlen NA. Rao, K. Rose

Deterministically annealed design of hidden Markov model speech recognizers

IEEE Trans. on Speech and Audio Processing, vol. 9, (no. 2), Feb. 2001

following article builds on the Neal & Hinton paper that we read last week. It tests an incremental version of EM (carefully choosing how incremental it will be), as well as a "lazy EM" version that visits "significant" cases more often. [9]
Apr. 25 Paul Ruhlen H. Al-Adhaileh, Kong, Melamed

Malay-English Bitext Mapping and Alignment Using SIMR/GSA Algorithms

Malaysian National Conference on Research and Development on Lingustics '2001

Fall 2001

Date/Time Presenter Paper(s) Supporting Papers/Notes
Dec. 14 Jia Cui Bellegarda

Exploiting latent semantic information in statistical language models

Proceedings of the IEEE , Volume: 88 Issue: 8 , Aug. 2000

Nov. 29 Silviu Cucerzan Mike Collins, Yoram Singer

Unsupervised Models for Named Entity Classification

EMNLP/VLC'99

Nov. 20 Radu Florian Blum, Mitchell

Combining Labeled and Unlabeled Data with Co-Training

Proceedings of 1998 Conference on Computational Learning Theory

Nov. 16 Richard Wicentowski Eisner, Satta

Efficient parsing for bilexical context-free grammars and head automaton grammars

ACL '99

plagiarism detection systems might be relevant to bitext alignment. A message to the Corpora list yesterday announced the following review paper:[10]
Nov. 2 Paul Ruhlen Manning, Schuetze

Foundations of Statistical Natural Language Processing, Section 14 on clustering, pp. 495-527.

MIT Press

Oct. 26 Gideon Mann Tishby, Pereira, Bialek

The information bottleneck method

The paper describes a clustering method which is a generalization of their earlier work on "Distributional Clustering of English Words" (pereira,tishby and lee '93).