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ICASSP
2011
IEEE
14 years 8 months ago
Similarity learning for semi-supervised multi-class boosting
In semi-supervised classification boosting, a similarity measure is demanded in order to measure the distance between samples (both labeled and unlabeled). However, most of the e...
Q. Y. Wang, Pong Chi Yuen, Guo-Can Feng
NIPS
2001
15 years 5 months ago
Probabilistic principles in unsupervised learning of visual structure: human data and a model
To find out how the representations of structured visual objects depend on the co-occurrence statistics of their constituents, we exposed subjects to a set of composite images wit...
Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Na...
EMNLP
2010
15 years 2 months ago
Lessons Learned in Part-of-Speech Tagging of Conversational Speech
This paper examines tagging models for spontaneous English speech transcripts. We analyze the performance of state-of-the-art tagging models, either generative or discriminative, ...
Vladimir Eidelman, Zhongqiang Huang, Mary P. Harpe...
GLOBECOM
2007
IEEE
15 years 10 months ago
Minimizing Distribution Cost of Distributed Neural Networks in Wireless Sensor Networks
Abstract—This paper presents a novel study on how to distribute neural networks in a wireless sensor networks (WSNs) such that the energy consumption is minimized while improving...
Peng Guan, Xiaolin Li
COLT
2003
Springer
15 years 9 months ago
Learning Random Log-Depth Decision Trees under the Uniform Distribution
We consider three natural models of random logarithmic depth decision trees over Boolean variables. We give an efficient algorithm that for each of these models learns all but an ...
Jeffrey C. Jackson, Rocco A. Servedio