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ML
2008
ACM
152views Machine Learning» more  ML 2008»
14 years 9 months ago
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
András Antos, Csaba Szepesvári, R&ea...
TEC
2008
135views more  TEC 2008»
14 years 9 months ago
Evolving Output Codes for Multiclass Problems
In this paper, we propose an evolutionary approach to the design of output codes for multiclass pattern recognition problems. This approach has the advantage of taking into account...
Nicolás García-Pedrajas, Colin Fyfe
ICML
2009
IEEE
15 years 10 months ago
Large margin training for hidden Markov models with partially observed states
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
Thierry Artières, Trinh Minh Tri Do
ICML
1999
IEEE
15 years 10 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
ATMOS
2007
177views Optimization» more  ATMOS 2007»
14 years 11 months ago
Approximate dynamic programming for rail operations
Abstract. Approximate dynamic programming offers a new modeling and algorithmic strategy for complex problems such as rail operations. Problems in rail operations are often modeled...
Warren B. Powell, Belgacem Bouzaïene-Ayari