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Laboratory of Computer and Information Science > Teaching > T-122.102 > Literature

T-122.102 Literature

[Under construction.]

  • "Oldies":
    • J measure, essentially the mutual information, and frequent sets:
      P. Smyth, R. M. Goodman, An information theoretic approach to rule induction from databases, IEEE Transactions on Knowledge and Data Engineering 4(4), 1992.
    • Maximum entropy methods, GIS:
      J. N. Darroch, D. Ratcliff, Generalized iterative scaling for log-linear models, The Annals of Mathematical Statistics 43(5) 1470-1480, 1972.
      J. Goodman, Sequential Conditional Generalized Iterative scaling, 2002. [CiteSeer]
  • Generative models:
    • Generative model, solved with MCMC:
      J.K. Pritchard, M. Stephens, P. Donnelly, "Inference of Population Structure Using Multilocus Genotype Data", 2000. [PDF] [10.2.2004]
    • Correlations added:
      D. Falush, M. Stephens, J. K. Pritchard, Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies, 2003. [PDF]
    • Basics of the variational method (LDA/mPCA):
      D. M. Blei, A. Y. Ng, M. I. Jordan, Latent Dirichlet Allocation, 2002. [CiteSeer]
      W. Buntine, Variational extensions to EM and Multinomial PCA, 2002. [CiteSeer]
    • LDA ja annotations:
      D. M. Blei, M. I. Jordan, Modeling annotated data, 2003. [PDF]
    • Theoretical basis, a different viewpoint:
      M. Collins, S. Dasgupta, R. E. Schapire, A generalization of principal component analysis to the exponential family, 2001. [CiteSeer]
    • Logistic PCA:
      A. I. Schein, L. K. Saul, L. H. Ungar, A Generalized Linear Model for Principal Component Analysis of Binary Data, 2003. [CiteSeer]
  • Mutual information related methods:
    • Basics:
      N. Tishby, F. C. Pereira, W. Bialek, The Information Bottleneck method, 1999. [CiteSeer]
    • IB applications, e.g.:
      N. Slonim, N. Friedman, N. Tishby, Unsupervised Document Classification using Sequential Information Maximixation, 2002. [CiteSeer]
      R. Bekkerman, R. El-Yaniv, N. Tishby, Y. Winter, Distributional word clusters vs. words for text categorization, 2003. [CiteSeer]
    • Projection functions:
      A. Globerson, N. Tishby, Sufficient dimensionality reduction, 2003. [PS]
    • Discriminative Clustering:
      J. Sinkkonen, S. Kaski, J. Nikkilä. Discriminative Clustering: Optimal Contingency Tables by Learning Metrics, 2002. [CiteSeer]
  • Kernel methods:
    • Survey:
      T. Gärtner, A Survey of Kernels for Structured Data, 2002. [PDF] [3.2.2004]
    • Fischer kernels:
      T. S. Jaakkola, D. Haussler, Exploiting Generative Models in Discriminative Classifiers, 1998. [CiteSeer]
      T. Jaakkola, M. Diekhans, D. Haussler, A discriminative framework for detecting remote protein homologies, 1998. [CiteSeer]
    • Information geometry:
      J. Lafferty, G. Lebanon, Information diffusion kernels, 2002. [CiteSeer]
      [Additionally something of information geometry?]
    • Other approaches:
      M. Seeger, Covariance kernels from Bayesian generative models, 2001. [CiteSeer]
      K. Tsuda, T. Kin, K. Asai, Marginalized kernels for biological sequences, 2002. [PDF]
  • Discretizing data:
    • H. Steck, T. S. Jaakkola, (Semi-)Predictive Discretization During Model Selection, 2003. [PS]
    • [To be added]

Friday, 17-Dec-2004 14:42:37 EET