Reference of the Thesis

Paper (read)：
L. Liao, D. J. Patterson, D. Fox, and H. Kautz. Learning and Inferring Transportation Routines. in Artificial Intelligence, 2007.
http://www.liaolin.com/Research/learning-transportations-aij-2007.pdf

L. Liao, D. Fox, and H. Kautz. Learning and Inferring Transportation Routines. in Proceedings of AAAI-04 , 2004. Outstanding Paper Award.
http://www.liaolin.com/Research/aaai2004.pdf

D. Patterson, L. Liao, D. Fox, and H. Kautz. Inferring High-Level Behavior from Low-Level Sensors. in Proceedings of The Fifth International Conference on Ubiquitous Computing (UBICOMP), 2003.
http://www.liaolin.com/Research/activity-compass-ubicomp-03.pdf


Paper (to be read)：
L. Liao, D. Fox, J. Hightower, H. Kautz and D. Schulz. Voronoi Tracking: Location Estimation Using Sparse and Noisy Sensor Data. in Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2003.
http://www.liaolin.com/Research/iros2003.pdf

L. Liao. Location-based Activity Recognition. University of Washington, 2006. (Ph.D. Thesis)
http://www.liaolin.com/Research/liao-thesis.pdf

L. Liao, D. J. Patterson, D. Fox, and H. Kautz. Building Personal Maps from GPS Data. in New York Academy of Sciences, 2007.

B. Limketkai, D. Fox, and L. Liao. CRF-filters: Conditional Particle Filters for Sequential State Estimation. in Proceedings of the International Conference on Robotics and Automation, 2007.
http://www.liaolin.com/Research/crf-filters-icra-07.pdf

A tutorial on hidden Markov models and selected applications in speech recognition
http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=698&arnumber=18626&count=9&index=1

Book:
1. Probabilistic robotics / Sebastian Thrun, Wolfram Burgard, Dieter Fox.

2. Sequential Monte Carlo methods in practice / Arnaud Doucet, Nando de Freitas, Neil Gordon.

3. Estimation with Applications to Tracking and Navigation / by Yaakov Bar-Shalom, X. Rong Li, Thiagalingam Kirubarajan.

4. Beyond the Kalman filter: particle filters for tracking applications / Branko Ristic, Sanjeev Arula.

5. Probabilistic reasoning in intelligent systems networks of plausible inference / Judea Pearl.

6. The EM algorithm and extensions / Geoffrey J. McLachlan, Thriyambakam Krishnan.


7. Tools for statistical inference methods for the exploration of posterior distributions and likelihoo functions / Martin A. Tanner.