Information retrieval and clustering using vector-based similarities
1 Computational Methods for Intelligent Information Access. M.W.
Berry, S.T. Dumais, and T.A. Letsche.Proceedings of Supercomputing'95,
San Diego, CA, December 1995.
http://www.supercomp.org/sc95/proceedings/473_MBER/SC95.HTM
1/18 linear algebra background _______Dan Boley____________________________
1/20 LSI example _______Dan Boley____________________________
2 Latent semantic indexing via a semi-discrete matrix decomposition
Tamara G. Kolda and Dianne P, O'Leary, in The Mathematics
of Information Coding, Extraction and Distribution, G. Cybenko et al.,
eds., vol. 107 of IMA Volumes in Mathematics and Its Applications.
Springer-Verlag, 1999, pp. 73-80.
http://csmr.ca.sandia.gov/~tgkolda/pubs/ACM-TOIS-1998.pdf
1/25 scalings; SDD variation _______Dan Boley____________________________
3 Concept Decompositions for Large Sparse Text Data using Clustering.
I.S. Dhillon, D.S. Modha, IBM Research Report RJ 10147, July 8, 1999,
Machine Learning, 42:1, pages 143-175, January 2001.
http://www.cs.utexas.edu/users/inderjit/public_papers/concept_mlj.pdf
1/27 alternative representation of dataset for text documents, matrix repr
_______Dan Boley________________(click here)
Link Analysis -- PageRank
6 The PageRank Citation Ranking: Bringing Order to the Web.Page,
Lawrence; Brin, Sergey; Motwani, Rajeev; Winograd, Terry. Stanford
Univ. Computer Science Dept technical report. Oct. 2001
http://dbpubs.stanford.edu/pub/1999-66
2/01 PageRank idea _____Rashid,Al Mamunur__________(click here)
8 Link Analysis, Eigenvectors and Stability, Andrew Y. Ng and Alice
X. Zheng and Michael I. Jordan. IJCAI 2001, p 903-910.
http://citeseer.ist.psu.edu/ng01link.html
2/03 numerical properties of PageRank _____Gkoulalas - Divanis,Aris___(click here)
robotics
2/08 Manuela Veloso, Computer Science Department, Carnegie Mellon
University, "Teams of Autonomous Robots: Perception, Cognition, and
Action." Talk in DTC at 5pm.
http://www.dtc.umn.edu/seminars/020805.html
Eigenfaces
9 Probabilistic Visual Learning for Object Representation, Baback
Moghaddam, Alex Pentland Early Visual Learning, Oxford University
Press, 1996.
http://citeseer.ist.psu.edu/moghaddam96probabilistic.html
2/10 face detection _____Agovic,Amrudin_____________(click here)
A View based and modular eigenspaces for face recognition.
A Pentland, B Moghaddam, T Starner.
IEEE Conf on Computer Vision & Pattern Recognition,
Seattle, June 1994.
http://ieeexplore.ieee.org/xpl/abs_free.jsp?arNumber=323814.
Alternate paper (with the same figures, intact):
http://citeseer.ist.psu.edu/moghaddam94face.html
2/15 face recognition _____Chrisopoulos,Vassilios_____(click here)
Basics of Eigenvalues, PCA definition
A tutorial on Principal Components Analysis
Lindsey I Smith
http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf&e=8092
2/17 PCA tutorial _______Dan Boley________________(click here)
Local Linear Embedding and visualization
B An Introduction to Locally Linear Embedding. Lawrence Saul & Sam
Roweis. [draft version (Jan.01)]
http://www.cs.toronto.edu/%7Eroweis/lle/papers/lleintro.pdf
2/22 Introduction to Locally Linear Embedding _____Kokiopoulou,Effrosyni_(click here)
Non-Negative Matrix Factorization
C Algorithms for Non-Negative Matrix Factorization. David Lee & H Sebastian
Seung.
hebb.mit.edu/people/seung/papers/nmfconverge.pdf
alternate paper:
Example of how SVD/PCA are used to analyse data - using example from Biology
[this is unusual in that I can read and understand it!!!!]
Singular value decomposition and principal component analysis.
Michael E. Wall
http://public.lanl.gov/mewall/kluwer2002.html
2/24 PCA in Biology _____Chen,Yanlai________________(click here)
Support Vector Machines
J Support Vector Machines: Hype or Hallelujah?, K. P. Bennett, C.
Campbell SIGKDD Explorations, Vol. 2, Issue 2, 2000.
http://www.acm.org/sigs/sigkdd/explorations/issue2-2/bennett.pdf
3/01 basic idea -- linear kernel primal problem _____Tran,Loc Hoang_____(click here)
3/03 VC Dimension, Generalization Bound _____Rashid,Al Mamunur__________(click here)
3/08 SVM Continued _____Kokiopoulou,Effrosyni______(click here)
Eigenvalue analysis
M Sepandar D. Kamvar, Dan Klein, and Christopher D. Manning,
"Spectral Learning", To appear in Proceedings of the Eighteenth
International Joint Conference on Artificial Intelligence, August
2003.
http://www.stanford.edu/~sdkamvar/papers/spectral.pdf
3/10 spectral clustering _____Boldt,Michael William______(click here)
Project Background Papers
Please provide a link to the paper you will discuss at least 2 days in advance
3/22 Laplacian Faces _____Kokiopoulou,Effrosyni______(click here)
3/24 ICA and Stock Data _____Boldt,Michael William______(click here)
3/29 SVM and face recognition _____Agovic,Amrudin_____________(click here)
3/31 To Be Announced _____Gkoulalas - Divanis,Aris___(click here)
4/05 To Be Announced _____Chrisopoulos,Vassilios_(click here)
4/07 To Be Announced _____Chen,Yanlai________________(click here)
4/12 Adaptive computation of PageRank _____Tran,Loc Hoang_____________(click here)
4/14 Information Theory _____Dan Boley_________(click here)
Project Progress Reports
4/19 Information-Theoretic CoClustering Dan Boley______________(click here)
4/21 To Be Announced _________________________________________
4/26 Project Presentation Effi_____________________________________
4/28 Project Presentation Michael__________Rudy____________________
5/03 Project Presentation Aris_____________Vassilis________________
5/05 Project Presentation Yanlai___________Loc_____________________