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    ATAL
    2007
    Springer
    143views Intelligent Agents» more  ATAL 2007»
    On discovery and learning of models with predictive representations of state for agents with continuous actions and observations
    15 years 10 months ago
    On discovery and learning of models with predictive representations of state for agents with continuous actions and observations
    Download  web.mit.edu
    Models of agent-environment interaction that use predictive state representations (PSRs) have mainly focused on the case of discrete observations and actions. The theory of discre...
    David Wingate, Satinder P. Singh
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    HYBRID
    2000
    Springer
    191views Control Systems» more  HYBRID 2000»
    A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
    15 years 10 months ago
    A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
    Download  www.ifp.illinois.edu
    Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
    Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
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    NIPS
    2008
    132views Information Technology» more  NIPS 2008»
    Learning with Consistency between Inductive Functions and Kernels
    15 years 7 months ago
    Learning with Consistency between Inductive Functions and Kernels
    Download  www.cs.rhul.ac.uk
    Regularized Least Squares (RLS) algorithms have the ability to avoid over-fitting problems and to express solutions as kernel expansions. However, we observe that the current RLS ...
    Haixuan Yang, Irwin King, Michael R. Lyu
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    205
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    IJCAI
    1989
    94views Artificial Intelligence» more  IJCAI 1989»
    Selective Learning of Macro-operators with Perfect Causality
    15 years 7 months ago
    Selective Learning of Macro-operators with Perfect Causality
    Download  dli.iiit.ac.in
    A macro-operator is an integrated operator consisting of plural primitive operators and enables a problem solver to solve more efficiently. However, if a learning system generates...
    Seiji Yamada, Sabinro Tsuji
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    159
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    ICMLA
    2009
    169views Machine Learning» more  ICMLA 2009»
    Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
    15 years 4 months ago
    Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
    Download  www.ipb.uni-bonn.de
    Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
    Johannes Hartz
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