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» An Introduction to Transfer Learning
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FLAIRS
2007
14 years 9 days ago
Knowledge Transfer in Deep Convolutional Neural Nets
Knowledge transfer is widely held to be a primary mechanism that enables humans to quickly learn new complex concepts when given only small training sets. In this paper, we apply ...
Steven Gutstein, Olac Fuentes, Eric Freudenthal
ICCV
2011
IEEE
12 years 10 months ago
Tabula Rasa: Model Transfer for Object Category Detection
Our objective is transfer training of a discriminatively trained object category detector, in order to reduce the number of training images required. To this end we propose three ...
Yusuf Aytar, Andrew Zisserman
ICONIP
2010
13 years 8 months ago
Improving Recurrent Neural Network Performance Using Transfer Entropy
Abstract. Reservoir computing approaches have been successfully applied to a variety of tasks. An inherent problem of these approaches, is, however, their variation in performance ...
Oliver Obst, Joschka Boedecker, Minoru Asada
STOC
1999
ACM
122views Algorithms» more  STOC 1999»
14 years 2 months ago
Oblivious Transfer and Polynomial Evaluation
Oblivious polynomial evaluation is a protocol involving two parties, a sender whose input is a polynomial P, and a receiver whose input is a value α. At the end of the protocol t...
Moni Naor, Benny Pinkas
AAAI
2008
14 years 9 days ago
Transferring Localization Models across Space
Machine learning approaches to indoor WiFi localization involve an offline phase and an online phase. In the offline phase, data are collected from an environment to build a local...
Sinno Jialin Pan, Dou Shen, Qiang Yang, James T. K...