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IROS
2008
IEEE
141views Robotics» more  IROS 2008»
15 years 6 months ago
Active sensing based dynamical object feature extraction
— This paper presents a method to autonomously extract object features that describe their dynamics from active sensing experiences. The model is composed of a dynamics learning ...
Shun Nishide, Tetsuya Ogata, Ryunosuke Yokoya, Jun...
IEEEPACT
2008
IEEE
15 years 6 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
MM
2009
ACM
269views Multimedia» more  MM 2009»
15 years 6 months ago
Semi-supervised topic modeling for image annotation
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...
ICANN
2011
Springer
14 years 3 months ago
Transforming Auto-Encoders
The artificial neural networks that are used to recognize shapes typically use one or more layers of learned feature detectors that produce scalar outputs. By contrast, the comput...
Geoffrey E. Hinton, Alex Krizhevsky, Sida D. Wang
AI
2005
Springer
15 years 5 months ago
A Supervised Learning Approach to Acronym Identification
This paper addresses the task of finding acronym-definition pairs in text. Most of the previous work on the topic is about systems that involve manually generated rules or regular ...
David Nadeau, Peter D. Turney