Ancient Papers (2001-2004)
-
L. Li, V. Bulitko, and R. Greiner: Focus of attention in sequential
decision making.
AAAI-04 Workshop on Learning and Planning in Markov Processes --- Advances
and Challenges, CA, July, 2004.
- L. Li, V. Bulitko, R. Greiner, and
I. Levner:
Improving an adaptive image interpretation system by leveraging.
Eighth Australian and New Zealand Conference on Intelligent
Information Systems, Sydney, Australia, December 2003.
- I. Levner, V. Bulitko, L. Li, G. Lee, and R. Greiner:
Learning robust object recognition
strategies.
To appear in the Eighth Australian and New Zealand Conference on Intelligent Information Systems, Sydney, Australia, December 2003.
- I. Levner, V. Bulitko, L. Li, G. Lee, and R. Greiner:
Automated feature extraction
for object recognition.
To appear in Image and Vision Computing'03
New Zealand, Palmerston North, New Zealand, November 2003.
- L Li, V Bulitko, R Greiner:
Batch Reinforcement Learning with State Importance;
ECML 2004.
- Active Model Selection
;
UAI 2004.
- J Newton and R Greiner,
Hierarchical Probabilistic
Relational Models for Collaborative Filtering;
SLR Workshop (ICML 2004).
- Proteome Analyst: Custom Predictions with Explanations in a
Web-based Tool for High-Throughput Proteome Annotations;
Nucleic Acid Research.
- The Budgeted Multi-Armed Bandit
Problem;
Open Problem Session, COLT-2004.
- Predictive Models for Breast Cancer Susceptibility from Multiple Single
Nucleotide Polymorphisms,
(w/J. Listgarten, S. Damaraju, B. Poulin, L. Cook,
J. Dufour, A. Driga, J. Mackey, D. Wishart, R. Greiner, and B. Zanke )
Clinical Cancer Reseach
- Predicting Sub-cellular Localization using
Machine-Learned Classifiers in Proteome Analyst,
(w/Z. Lu, D. Szafron, D. Wishart, B. Poulin, J. Anvik,
C. Macdonell, and R. Eisner)
Bioinformatics
- I. Levner, V. Bulitko, L. Li, G. Lee, R Greiner:
Towards Automated Creation of Image Interpretation Systems
Australian
Joint Artificial Intelligence Conference
-
Discriminative Parameter Learning of General Bayesian Network Classifiers,
(w/B. Shen, X. Su, P. Musilek, C. Cheng),
15th IEEE International Conference on Tools with Artificial Intelligence
- Adaptive Image Interpretation: A
Spectrum Of Machine Learning Problems,
(w/V. Bulitko, L. Li, G. Lee, G. and I. Levner)
ICML Workshop on The Continuum from Labeled to Unlabeled Data in
Machine Learning and Data Mining
- Proteome Analyst -- Transparent
High-throughput Protein Annotation: Function, Localization and Custom
Predictors
(w/D. Szafron, P. Lu, D. Wishart, Z. Lu, B. Poulin, R. Eisner, J. Anvik and
C. Macdonell)
ICML 2003 Workshop: Machine Learning in Bioinformatics
- Budgeted
Learning of Naive-Bayes Classifiers,
(w/D. Lizotte and O. Madani)
UAI03
- Use of Off-line Dynamic Programming in Efficient Image Interpretation,
(w/R. Isukapalli)
IJCAI'2003
- Lookahead Pathologies for Single Agent
Search (w/V. Bulitko, L. Li and I. Levner)
IJCAI'2003
- An Effective Complete-Web
Recommender System (w/T. Zhu, G. Häubl)
WWW'2003
- Predicting Where a Web User Wants to
Go (w/T. Zhu, G. Häubl)
CHI 2003 Worshop
- Learning a Model of a Web User's
Interests (w/T. Zhu, G. Häubl)
UM'2003
- Learning Cost-Sensitive Active
Classifiers (w/A. Grove, D. Roth).
Artificial Intelligence
- Learning Cost-Sensitive Active Classifiers (w/A. Grove, D. Roth).
Artificial Intelligence,
139:2, pp. 137-174, Sept 2002.
- Learning Bayesian Networks from Data: An Information-Theory Based Approach, (w/J. Cheng, J. Kelly, D. Bell, W. Liu)
Artificial Intelligence, 2002.
- Medical Resonance Diagnostics - A New Technology for High Throughput Clinical Diagnostics, (w/D. Wishart, L. Querengesser, B. Lefebvre, N. Epstein,J. Newton).
Journal of Clinical Chemistry, 2001.
- Efficient Reasoning, (w/C. Darken, N. I. Santoso).
Computing Surveys, 33:1 (March 2001), p. 1-30.
- Structural extension to logistic regression: Discriminative Parameter Learning of Belief Net Classifiers, (w/W. Zhou).
AAAI-02.
- Optimal Depth-First Strategies for
And-Or Trees, (w/R. Hayward, M. Malloy).
PPT poster (draft)
AAAI-02.
- Bayesian Error-Bars for Belief Net Inference, (w/T. Van Allen, P. Hooper).
UAI-01.
- Efficient Interpretation Policies, (w/R. Isukapalli).
IJCAI-01.
- Learning Bayesian Belief Network Classifiers: Algorithms and System, (w/J. Cheng).
CSCSI-01.Runner-Up, Best Paper Prize
- On Models of Control and Lookahead Search for Image Interpretation, (w/O. Madani, V. Bulitko, I. Levner).
SARA'02
- Real-time Lookahead Control Policies, (w/V. Bulitko, I. Levner).
Workshop: Real-Time Decision Support and Diagnosis Systems
- Efficient Car Recognition Policies, (w/R. Isukapalli).
ICRA01.
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