421 search results - page 42 / 85 » Incorporating Test Inputs into Learning |
72
Voted
NIPS
2008
14 years 11 months ago
2008
Randomized neural networks are immortalized in this well-known AI Koan: In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What a...
GPEM
2002
14 years 9 months ago
2002
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
PRL
2011
14 years 4 months ago
2011
In some real world applications, such as spectrometry, functional models achieve better predictive performances if they work on the derivatives of order m of their inputs rather t...
INTERSPEECH
2010
14 years 4 months ago
2010
In an attempt to improve models of human perception, the recognition of phonemes in nonsense utterances was predicted with automatic speech recognition (ASR) in order to analyze i...
84
Voted
NIPS
1997
14 years 11 months ago
1997
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...