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» Unbundling Active Functionality
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PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
14 years 4 months ago
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Manuel Lopes, Francisco S. Melo, Luis Montesano
VLDB
2002
ACM
126views Database» more  VLDB 2002»
13 years 9 months ago
ALIAS: An Active Learning led Interactive Deduplication System
Deduplication, a key operation in integrating data from multiple sources, is a time-consuming, labor-intensive and domainspecific operation. We present our design of alias that us...
Sunita Sarawagi, Anuradha Bhamidipaty, Alok Kirpal...
GECCO
2010
Springer
152views Optimization» more  GECCO 2010»
14 years 2 months ago
Active covariance matrix adaptation for the (1+1)-CMA-ES
We propose a novel variant of the (1 + 1)-CMA-ES that updates the distribution of mutation vectors based on both successful and unsuccessful trial steps. The computational costs o...
Dirk V. Arnold, Nikolaus Hansen
CHI
1998
ACM
14 years 2 months ago
Cognitive Function Analysis for Human-Centered Automation of Safety-Critical Systems
The Cognitive Function Analysis is a methodology supportedby a mediating tool for the human-centered automationof safety-critical systems[4]. It is basedon a socio-cognitive model...
Guy A. Boy
CSMR
1999
IEEE
14 years 2 months ago
Impact of Function Pointers on the Call Graph
Maintenance activities are made more difficult when pointers are heavily used in source code: the programmer needs to build a mental model of memory locations and of the way they ...
Giuliano Antoniol, F. Calzolari, Paolo Tonella