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CVPR
2005
IEEE
16 years 8 months ago
A Bayesian Hierarchical Model for Learning Natural Scene Categories
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent t...
Fei-Fei Li 0002, Pietro Perona, California Institu...
TACAS
2007
Springer
117views Algorithms» more  TACAS 2007»
16 years 23 days ago
Replaying Play In and Play Out: Synthesis of Design Models from Scenarios by Learning
This paper is concerned with bridging the gap between requirements, provided as a set of scenarios, and conforming design models. The novel aspect of our approach is to exploit lea...
Benedikt Bollig, Joost-Pieter Katoen, Carsten Kern...
HICSS
2002
IEEE
155views Biometrics» more  HICSS 2002»
15 years 11 months ago
Towards Knowledge-Sharing and Learning in Virtual Professional Communities
This paper describes a program of research designed to understand how knowledge-sharing and learning can be supported in virtual communities. To conduct this research, we propose ...
Michael Bieber, Il Im, Ronald E. Rice, Ricki Goldm...
CIA
2006
Springer
15 years 10 months ago
Learning to Negotiate Optimally in Non-stationary Environments
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
Vidya Narayanan, Nicholas R. Jennings
CIVR
2006
Springer
186views Image Analysis» more  CIVR 2006»
15 years 10 months ago
Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...