University of Florida

Date

Presenter

Paper

14th August

Seniha Esen Yuksel

"Steve Waterhouse, David Mackay, Tony Robinson; "Bayesian Methods for Mixtures of Experts," Advances in Neural Information Processing Systems, 1996.

7th August

Seniha Esen Yuksel

"S.R. Waterhouse, A.J. Robinson; "Classification using hierarchical mixtures of experts," Neural Networks for Signal Processing [1994] IV. Proceedings of the 1994 IEEE Workshop 6-8 Sept. 1994 Page(s):177 - 186

20th June

Raazia Mazhar

"Optimized Dictionary Design and Classification using The Matching Pursuits Based Dissimilarity Measure"

Date

Presenter

Paper

24th April

Seniha Esen Yuksel

Michael I. Jordan and Robert A. Jacobs, "Hierarchical Mixtures of Experts and the EM Algorithm," Massachusetts Institute of Technology, Artificial Intelligence Laboratory

18th April

Jeremy Bolton

"Random Set Model for Context-Based Classification," Thesis proposal.

17th April

Ryan Busser

V. C. Raykar, R. Duraiswami, B. Krishnapuram, "A fast algorithm for learning large scale preference relations," International Conference on Artificial Intelligence and Statistics (AISTATS), Puerto Rico, March 2007, vol. 2, pp. 388-395, March 2007

6th March

Fei Xu

"Simultaneous Inference and Database Sampling."

4th March

Gyeongyong Heo

"Spectral Graph Theory and Spectral Clustering," based on the following papers:
1. Ulrike von Luxburg, "A Tutorial on Spectral Clustering," Statistics and Computing 17(4), 2007
2. Igor Fischer and Jan Poland, "Amplifying the Block Matrix Structure for Spectral Clustering," Technical Report, 2005

28th February

Gyeongyong Heo

"Spectral Graph Theory and Spectral Clustering," based on the following papers:
1. Ulrike von Luxburg, "A Tutorial on Spectral Clustering," Statistics and Computing 17(4), 2007
2. Igor Fischer and Jan Poland, "Amplifying the Block Matrix Structure for Spectral Clustering," Technical Report, 2005

14th February

Jeremy Bolton

"Random Set Model for Context-Based Classification"

31st January

Raazia Mazhar

H. Frigui & R. Krishnapuram, "Clustering by Competitive Agglomeration," Pattern Recognition, vol. 30, no. 7, pp. 1109-1119, July 1997

17th January

Ganesan Ramachandran

X. Ma, D. Schonfeld, and A. Khokhar, "A General Two-Dimensional Hidden Markov Model and its Application in Image Classification," IEEE International Conference on Image Processing, San Antonio, Texas, 2007

Date

Presenter

Paper

27th November

Alina Zare

Teh, Y.W., Gorur, D. and Ghahramani, Z., "Stick-breaking Construction for the Indian Buffet," Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-2007), San Juan, Puerto Rico, 2007

20th November

Sudhir Rao

Finding Structure in Data: The central goal of unsupervised learning is to discover the underlying structure and patterns in the data. Since the type of structure varies with the data, we instead define a "goal" to extract those patterns which are useful in accomplishing it by constructing a global objective function. In doing so, we internally derive a teaching signal from the data itself through the principle of self organization. With the "goal" embedded in the cost function, these local forces define the rules of interaction between the data particles. Self organization of these particles should then reveal the structure in the data relevant to this goal. In this talk, I will be show how information theoretic learning principles can be used to derive these self organizing rules. A new information theoretic framework for unsupervised learning will be presented. In particular, the mean shift algorithms appear as special cases under this general framework giving them a whole new perspective. We will see how this framework could be applied to wide variety of applications ranging from clustering, principal curves to vector quantization.

13th November

Sean Matthews

Sato, M., Takahashi, K., Fujiwara, J., "Development of the Hand held dual sensor ALIS and its evaluation," 4th International Workshop on Advanced Ground Penetrating Radar 2007, 27-29 June 2007, Pages: 3-7

6th November

Seniha Esen Yuksel

R. Jenssen, K.E. Hild, , D. Erdogmus, J.C. Principe, T. Eltoft, "Clustering using Renyi's entropy," Image Proceedings of the International Joint Conference on Neural Networks, July 2003

30th October

Raazia Mazhar

Phillips, P.J., "Matching pursuit filters applied to face identification," Image Processing, IEEE Transactions on, vol. 7, no. 8, pp. 1150-1164, August 1998

16th October

Xuping Zhang

1. Petar M. Djuric, Joon-Hwa Chun, "An MCMC Sampling Approach to Estimation of Nonstationary Hidden Markov Models," IEEE Trans. Signal Process., vol. 50, no. 5, pp. 1113-1123, May 2002
2. Zoubin Ghahrammani, "An Introduction to Hidden Markov Models and Bayesian Networks," International Journal of Pattern Recognition and Artificial Intelligence 15(1):9-42
3. Olivier Cappe, Eric Moulines, Tobias Ryden, "Inference in Hidden Markov Models," Springer Book, 2005

9th October

Ryan Busser

Freund, Y., Iyer, R., Schapire, R.E., Singer, Y., "An Efficient Boosting Algorithm for Combining Preferences," Journal of Machine Learning Research, 4 (2003) 933-969, 2003

2nd October

Gyeongyong Heo

1. R. Krishnapuram and J.M. Keller, "A Possibilistic Approach to Clustering," IEEE Transactions on Fuzzy Systems 1(2), pp. 98-110
2. N.R. Pal, K. Pal, J.M. Keller and J.C. Bezdek, "A Possibilistic Fuzzy c-Means Clustering Algorithm," IEEE Transactions on Fuzzy Systems 13(4),pp. 517-530, 2005
3. D.E. Gustafson and W.C. Keller, "Fuzzy clustering with a fuzzy covariance matrix," Proceedings of the 1978 IEEE Conference on Decisionand Control, pp. 761-766, 1979
4. I. Gath and A.B. Geva, "Unsupervised Optimal Fuzzy Clustering," IEEE  Transactions on Pattern Analysis and Machine Intelligence 11(7), pp.773-781, 1989

25th September

Raazia Mazhar

1. Teh, Y.W., Jordan, M.I., Beal M.J. and Blei, D.M, "Hierarchical Dirichlet Processes," Journal of the American Statistical Association, 2006
2. Teh, Y.W., Jordan, M.I., Beal M.J. and Blei, D.M, "Using Dependent Regions for Object Categorization in a Generative Framework," Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, Volume 2, 2006 Page(s):1597 - 1604

18th September

Raazia Mazhar

Teh, Y.W., Jordan, M.I., Beal M.J. and Blei, D.M, "Using Dependent Regions for Object Categorization in a Generative Framework," Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, Volume 2, 2006 Page(s):1597 - 1604

Date

Presenter

Paper

12th June

Andres Mendez-Vazquez

Dongxin Xu, Jose C. Principe, "Learning from Examples with Quadratic Mutual Information"

5th June

Ganesan Ramachandran

Dongxin Xu, Jose C. Principe, "Reject Option in Pattern Recognition : Overview and new Advances"

29th May

Alina Zare

1. S. Jain and R. M. Neal, "A Split-Merge Markov Chain Monte Carlo Procedure for Dirichlet Process Mixture Model"
2. A. Ranganathan, "The Dirichlet Process Mixture (DPM) Model"

22nd May

Alina Zare

1. S. Jain and R. M. Neal, "A Split-Merge Markov Chain Monte Carlo Procedure for Dirichlet Process Mixture Model"
2. A. Ranganathan, "The Dirichlet Process Mixture (DPM) Model"

8th May

Ganesan Ramachandran

1. Rathinavelu, C. Deng, L, "Use of Generalized Dynamic Feature Parameters for Speech Recognition"
2. Mario A.T. Figueiredo, "Adaptive Sparseness for Supervised Learning"

Date

Presenter

Paper

24th April

Alina Zare

J. Borges, J. Bioucas-Dias, and A. Marçal, "Bayesian Hyperspectral Image Segmentation with Discriminative Class Learning," in Pattern Recognition and Image Analysis: 3rd Iberian Conference, IbPRIA 2007, Lecture Notes in Computer Science, Girona, Spain, 2007

17th April

Xuping Zhang

Jenssen, R., Eltoft, T., Girolami, M. and Erdogmus, D., "Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm"

9th April

Gyeongyong Heo

David J.C. MacKay, "Ensemble learning for hidden Markov models," Technical Report, 1997

27th March

Gyeongyong Heo

David J.C. MacKay, "Ensemble learning for hidden Markov models," Technical Report, 1997

20th March

Dr. Yijun Sun

Yijun Sun, "Iterative RELIEF for Feature Weighting: Algorithms, Theories, and Applications," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 6, June 2007

13th March

Jeremy Bolton

1. Rubner, Y. , Tomasi, C. and Guibas, L.J., "A Metric for Distributions with Applications to Image Databases"
2. Kwok-Leung Tam, Lau, R.W.H. and Chong-Wah Ngo, "Deformable geometry model matching by topological and geometric signatures," Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, 23-26 Aug. 2004, Volume: 3, On page(s): 910- 913 Vol.3
3. Krahnstoever, N.; Sharma, R., "Robust probabilistic estimation of uncertain appearance for model-based tracking," Motion and Video Computing, 2002. Proceedings. Workshop on , vol., no., pp. 28-33, 5-6 Dec. 2002
4. Rubner, Y., Guibas, L. and Tomasi, C. "The Earth Mover's Distance, Multi-Dimensional Scaling, and. Color-Based Image Retrieval" Motion and Video Computing, 2002. Proceedings. Workshop on , vol., no., pp. 28-33, 5-6 Dec. 2002

6th March

Raazia Mazhar

Aahron M., Elad M., Bruckstein A., "K-SVD An Algorithm for Designing Overcomplete Dictionaries for Sparse represenation," IEEE transactions on Signal Processing, vol 54, no. 11, November 2006

12th February

Ganesan Ramachandran

Inoue, M., Ueda, N., "Exploitation of Unlabeled Sequences in Hidden Markov Models" Pattern Analysis and Machine Intelligence, IEEE Transactions on Volume 25, Issue 12, Dec. 2003 Page(s): 1570 - 1581

23rd January

Gyeongyong Heo

"Dirichlet Processes and its Extensions"

16th January

Gyeongyong Heo

"Dirichlet Processes and its Extensions"