CS 598 Signals AI

Notes

1. Week 1: Intro

   My notes

2. Week 2: Collocations in Language and Vision

   My notes

3. Week 3 was paper discussions
4. Week 4:  No week 4, instructor ill
5. Week 5: Smoothing and dynamical models

   My notes

6. Week 6: More smoothing and dynamical models, paper discussion
7. Week 7: more paper discussion, started Regression and classification  My notes
8. Week 12: Correspondence  My Notes
9. Week 15: Parsing  My Notes
   

Resources

1. Natural Language books

• Chris Manning, Hinrich Schutze, Foundations of statistical natural language processing, MIT press, 1999
• Dan Jurafsky, James Martin, Speech and Language Processing, Prentice-Hall, 2000

1. Computer Vision books

• David Forsyth, Jean Ponce, Computer Vision - A Modern Approach, Prentice Hall, 2002

Reading

1. Collocations in Language and Vision
   • Frank Smadja , Kathleen McKeown, Translating collocations for use in bilingual lexicons, Proceedings of the workshop on Human Language Technology, March 08-11, 1994, Plainsboro, NJ
   • Frank Smajda, Retrieving collocations from text: Xtract,   Computational Linguistics archive
     Volume 19 ,  Issue 1  (March 1993) Pages: 143 - 177  
   • Peter D. Turney, Michael L Littman, Measuring praise and criticism: Inference of semantic orientation from association, Volume 21 ,  Issue 4  (October 2003) Pages: 315 - 346  
   • A. Kilgarriff and T. Rose, Measures for corpus similarity and homogeneity, In proceedings of the 3 rd conference on Empirical Methods in Natural Language Processing, Granada, Spain, pp. 46 - 52, 1998
   • Local Greyvalue Invariants for Image Retrieval. C. Schmid and R. Mohr. In Pattern Analysis and Machine Intelligence, 1997
   • Discovering Objects and Their Location in Images J. Sivic, B. Russell, A.A. Efros, A. Zisserman, and W.T. Freeman, International Conference on Computer Vision (ICCV 2005), October, 2005.   
2. Dynamical models in Language and Vision
   • L. Rabiner, B. Juang, An introduction to hidden Markov models, IEEE ASSP Magazine, 1986, pp 4-16
     
   • B. H. Juang; L. R. Rabiner, Hidden Markov Models for Speech Recognition, Technometrics, Vol. 33, No. 3. (Aug., 1991), pp. 251-272
   • Oliver, N.M.   Rosario, B.   Pentland, A.P., A Bayesian computer vision system for modeling human interactions, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2000, 831-843
     
   • D Cutting, J Kupiec, J Pedersen, P Sibun, A practical part-of-speech tagger, Proceedings of the third conference on Applied natural language processing, 133-140, 1992
     
   • E. Brill, A simple rule-based part of speech tagger, Proceedings of the workshop on Speech and Natural Language, 112 - 116,  1992
     
   • Starner, T.   Weaver, J.   Pentland, A.   Real-time American sign language recognition using desk andwearable computer based video
     Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1371-1375, 1998
   • Ali Farhadi, David Forsyth, Ryan White, "Transfer Learning in Sign Language," IEEE Conference on Computer Vision and Pattern Recognition, 2007
   • Nazli Ikizler and David Forsyth, “Searching video for complex activities with finite state models” IEEE Conference on Computer Vision and Pattern Recognition, 2007
   • O. Boiman  and   M. Irani, Detecting Irregularities in Images and in Video.   IEEE International Conference on Computer Vision (ICCV), Beijing, October 2005.
   • L. Zelnik-Manor  and  M. Irani,  Statistical Analysis of Dynamic Actions. IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 28(9): 1530--1535, September 2006. 
   • Alexei A. Efros, Alexander Berg, Greg Mori, Jitendra Malik, Recognizing Action at a Distance, In ICCV 2003
   • "Searching for Character Models", Jaety Edwards, D.A. Forsyth, NIPS 2005
   • "Making Latin Manuscripts Searchable using gHMM's", Jaety Edwards, Yee-Whye Teh, D.A. Forsyth, Roger Bock, Michael Maire, Grace Vesom, NIPS 2004
3. Correspondence reasoning in language and vision
• Kobus Barnard, Pinar Duygulu, Nando de Freitas, David Forsyth, David Blei, and Michael I. Jordan, "Matching Words and Pictures", Journal of Machine Learning Research, Vol 3, pp 1107-1135. 2003   
• Oded Maron, Aparna Lakshmi Ratan, Multiple-Instance Learning for Natural Scene Classification (1998) 
   Proc. 15th International Conf. on Machine Learning
• S Andrews, I Tsochantaridis, T Hofmann, Support vector machines for multiple-instance learning
  - Advances in Neural Information Processing Systems, 2002
• PF Brown, SD Pietra, VJD Pietra, RL Mercer, The Mathematic of Statistical Machine Translation: Parameter Estimation,
   Computational Linguistics, 1994
• K Yanai, K Barnard, Image region entropy: a measure of" visualness" of web images associated with one concept
  Proceedings of the 13th annual ACM international conference on multimedia, 2005
• B. Scholkopf, A. Smola, K-R Muller, ``Nonlinear Component Analysis as a Kernel Eigenvalue Problem,'' Neural Computation 10, 1299-1319 (1998)
• T. Berg, A. Berg, J. Edwards, M. Maire, R. White, Y-W Teh, E. Learned-Miller, D.A. Forsyth, Names and Faces, in review, 2007.