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CVPR
1997
IEEE
15 years 11 months ago
Learning Generic Prior Models for Visual Computation
This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling t...
Song Chun Zhu, David Mumford
CHI
2010
ACM
15 years 11 months ago
Designing games for learning: insights from conversations with designers
This paper presents insights about design practices that can lead to effective and fun games for learning, gleaned from interviews with experienced game developers. We based our a...
Katherine Isbister, Mary Flanagan, Chelsea Hash
ICANN
2007
Springer
15 years 11 months ago
Active Learning to Support the Generation of Meta-examples
Meta-Learning has been used to select algorithms based on the features of the problems being tackled. Each training example in this context, i.e. each meta-example, stores the feat...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
ICANN
2009
Springer
15 years 11 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft
COLT
2006
Springer
15 years 11 months ago
Online Learning with Constraints
In this paper, we study a sequential decision making problem. The objective is to maximize the total reward while satisfying constraints, which are defined at every time step. The...
Shie Mannor, John N. Tsitsiklis