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Abstract: We advocate the learning of compositional hierarchies in predictive models, an area we feel is signi cantly underrepresented in machine learning, especially in general forms. Simultaneously, we present a basic unsupervised learning paradigm for sequential or spatial domains that generalizes the most closely related learning problems. We argue that there are useful synergies between this problem and the goal of learning predictive compositional hierarchies. The core aim of learning... (Update)
Context of citations to this paper: More
.... prediction patterns, such as predicting a middle symbol from context on both sides or simultaneously predicting multiple symbols [5]. This generality necessitates representing estimates for the full joint distribution rather than the conditional distribution. Accuracy...
...representational units to include. We propose hierarchical composition of known frequent patterns as a general solution to this problem [7]. In contrast to on line learning of multiwidth tree mixtures [10, 6] our hierarchical sparse n grams can grow with no prespecified bound...
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BibTeX entry: (Update)
K. Pfleger. Learning predictive compositional hierarchies. In Proceedings of the AAAI2000 workshop on New Research Problems for Machine Learning, 2000. To appear. See www-cs-students.stanford.edu/kpfleger/publications/. http://citeseer.ist.psu.edu/article/pfleger00learning.html More
@misc{ pfleger00learning,
author = "K. Pfleger",
title = "Learning predictive compositional hierarchies",
text = "K. Pfleger. Learning predictive compositional hierarchies. In Proceedings
of the AAAI2000 workshop on New Research Problems for Machine Learning,
2000. To appear. See www-cs-students.stanford.edu/kpfleger/publications/.",
year = "2000",
url = "citeseer.ist.psu.edu/article/pfleger00learning.html" }
Citations (may not include all citations):2319 Elements of Information Theory (context) - Cover, Thomas - 1991
371 Explanation-based generalization: A unifying view (context) - Mitchell, Keller et al. - 1986
368 Text Compression (context) - Bell, Cleary et al. - 1990
328 Foundations of Statistical Natural Language Processing - Manning, Schutze - 1999
301 Neural networks and the bias/variance dilemma (context) - Geman, Bienenstock et al. - 1992
199 A model for reasoning about persistence and causation (context) - Dean, Kanazawa - 1989
145 Chunking in soar: The anatomy of a general learning mechanis.. (context) - Laird, Rosenbloom et al. - 1986
115 The parti-game algorithm for variable resolution reinforceme.. - Moore, Atkeson - 1995
102 Neurocomputing: Foundations of Research (context) - Anderson, Rosenfeld - 1988
85 The second naive physics manifesto (context) - Hayes - 1985
82 Cyc: A midterm report (context) - Guha, Lenat - 1990
80 Readings in Machine Learning (context) - Shavlik, Dietterich - 1990
74 Blackboard systems: The blackboard model of problem solving .. (context) - Nii - 1986
61 Unbounded length contexts for ppm - Cleary, Teahan - 1997
48 Inducing probabilistic grammars by bayesian model merging - Stolcke, Omohundro - 1994
41 Boltzmann chains and hidden markov models - Saul, Jordan - 1994
31 Discrete sequence prediction and its applications (context) - Laird, Saul - 1994
18 Inferring Sequential Structure (context) - Nevill-Manning - 1996
17 Bayesian unsupervised learning of higher order structure - Lewicki, Sejnowski - 1997
16 Learning to predict sequences (context) - Dietterich, Michalski - 1986
10 Identifying hierarchical structure in sequences: a lineartim.. (context) - Nevill-Manning, Witten - 1997
5 Unied Theories of Cognition (context) - Newell - 1990
5 AI Magazine (context) - Nilsson, the - 1995
4 An interactive activation model of context e ects in letter .. (context) - McClelland, Rumelhart - 1981
3 Bayesian classication with correlation and inheritance (context) - Hanson, Stutz et al. - 1991
3 An algorithm for the segmentation of an articial language an.. (context) - Wol - 1975
3 Feature selection and incremental learning of probabilistic .. - Talavera - 2000
3 acQuire-macros: An algorithm for automatically learning macr.. - McGovern - 1998
3 Learning with probabilistic representations (context) - Langley, Provan et al. - 1997
2 Learning of compositional hierarchies for the modeling of co.. (context) - eger - 1997
2 An introduction to blackboard-style systems organization (context) - eger, Hayes-Roth - 1997
1 Learning hierarchical behaviors - Andre - 1998
1 Learning context-free grammars with a simplicity bias - Langley, Stromsten - 2000
1 Hierarchical unsupervised learning (context) - Vaithyanathan, Dom - 2000
1 Presented at the ICML Workshop on Machine Learning from Sequ.. (context) - eger - 2000
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