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ICML
2005
IEEE
16 years 5 months ago
Exploration and apprenticeship learning in reinforcement learning
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
Pieter Abbeel, Andrew Y. Ng
CVPR
2000
IEEE
16 years 6 months ago
Learning from One Example through Shared Densities on Transforms
We define a process called congealing in which elements of a dataset (images) are brought into correspondence with each other jointly, producing a data-defined model. It is based ...
Erik G. Miller, Nicholas E. Matsakis, Paul A. Viol...
MICCAI
2008
Springer
16 years 5 months ago
Classification of Suspected Liver Metastases Using fMRI Images: A Machine Learning Approach
Abstract. This paper presents a machine-learning approach to the interactive classification of suspected liver metastases in fMRI images. The method uses fMRI-based statistical mod...
Moti Freiman, Yifat Edrei, Yehonatan Sela, Yitz...
SOUPS
2009
ACM
15 years 11 months ago
Machine learning attacks against the Asirra CAPTCHA
The ASIRRA CAPTCHA [6], recently proposed at ACM CCS 2007, relies on the problem of distinguishing images of cats and dogs (a task that humans are very good at). The security of AS...
Philippe Golle
AVSS
2007
IEEE
15 years 11 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen