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CONCUR
2006
Springer
15 years 6 months ago
Minimization, Learning, and Conformance Testing of Boolean Programs
Boolean programs with recursion are convenient abstractions of sequential imperative programs, and can be represented as recursive state machines (RSMs) or pushdown automata. Motiv...
Viraj Kumar, P. Madhusudan, Mahesh Viswanathan
117
Voted
DATAMINE
2002
125views more  DATAMINE 2002»
15 years 2 months ago
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
13 years 4 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
122
Voted
ECML
2006
Springer
15 years 6 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
CORR
2010
Springer
147views Education» more  CORR 2010»
15 years 2 months ago
Learning Probabilistic Hierarchical Task Networks to Capture User Preferences
While much work on learning in planning focused on learning domain physics (i.e., action models), and search control knowledge, little attention has been paid towards learning use...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...