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CVPR
2008
IEEE
16 years 6 months ago
Learning stick-figure models using nonparametric Bayesian priors over trees
We present a fully probabilistic stick-figure model that uses a nonparametric Bayesian distribution over trees for its structure prior. Sticks are represented by nodes in a tree i...
Edward Meeds, David A. Ross, Richard S. Zemel, Sam...
ICANN
2009
Springer
15 years 10 months ago
Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction
Abstract. In this paper, we investigate the application of adaptive ensemble models of Extreme Learning Machines (ELMs) to the problem of one-step ahead prediction in (non)stationa...
Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutil...
ICTAI
2007
IEEE
15 years 10 months ago
ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming
In this paper we developed an Inductive Logic Programming (ILP) based framework ExOpaque that is able to extract a set of Horn clauses from an arbitrary opaque machine learning mo...
Yunsong Guo, Bart Selman
174
Voted
NIPS
2008
15 years 5 months ago
A "Shape Aware" Model for semi-supervised Learning of Objects and its Context
We present an approach that combines bag-of-words and spatial models to perform semantic and syntactic analysis for recognition of an object based on its internal appearance and i...
Abhinav Gupta, Jianbo Shi, Larry S. Davis
ACL
2003
15 years 5 months ago
Unsupervised Learning of Dependency Structure for Language Modeling
This paper presents a dependency language model (DLM) that captures linguistic constraints via a dependency structure, i.e., a set of probabilistic dependencies that express the r...
Jianfeng Gao, Hisami Suzuki