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GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 2 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
ICGI
2004
Springer
14 years 1 months ago
Learning Stochastic Finite Automata
Abstract. Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We report here a number of results concerning the learnability of th...
Colin de la Higuera, José Oncina
ACL
1997
13 years 9 months ago
Finite State Transducers Approximating Hidden Markov Models
This paper describes the conversion of a Hidden Markov Model into a sequential transducer that closely approximates the behavior of the stochastic model. This transformation is es...
André Kempe
WINE
2007
Springer
124views Economy» more  WINE 2007»
14 years 1 months ago
Stochastic Models for Budget Optimization in Search-Based Advertising
Internet search companies sell advertisement slots based on users’ search queries via an auction. Advertisers have to solve a complex optimization problem of how to place bids o...
S. Muthukrishnan, Martin Pál, Zoya Svitkina
RTAS
2007
IEEE
14 years 2 months ago
Stochastic Metrics for Debugging the Timing Behaviour of Real-Time Systems
Stochastic analysis techniques for real-time systems model the execution time of tasks as random variables. These techniques constitute a very powerful tool to study the behaviour...
Joaquín Entrialgo, Javier García, Jo...