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ICCV
2007
IEEE
16 years 2 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
110
Voted
CVPR
2007
IEEE
16 years 2 months ago
Towards Scalable Representations of Object Categories: Learning a Hierarchy of Parts
This paper proposes a novel approach to constructing a hierarchical representation of visual input that aims to enable recognition and detection of a large number of object catego...
Sanja Fidler, Ales Leonardis
130
Voted
AAAI
2006
15 years 1 months ago
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Shimon Whiteson, Peter Stone
CHI
1999
ACM
15 years 4 months ago
Bridging Strategies for VR-Based Learning
A distributed immersive virtual environment was deployed as a component of a pedagogical strategy for teaching third grade children that the Earth is round. The displacement strat...
Thomas G. Moher, Andrew E. Johnson, Stellan Ohlsso...
UAI
1998
15 years 1 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell