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» Unbundling Active Functionality
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PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
15 years 9 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
108
Voted
VLDB
2002
ACM
126views Database» more  VLDB 2002»
15 years 2 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...
91
Voted
GECCO
2010
Springer
152views Optimization» more  GECCO 2010»
15 years 6 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
105
Voted
CHI
1998
ACM
15 years 6 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
15 years 6 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