Multitask learning
R Caruana - Machine learning, 1997 - Springer
Multitask Learning is an approach to inductive transfer that improves generalization by using
the domain information contained in the training signals of related tasks as an inductive bias …
the domain information contained in the training signals of related tasks as an inductive bias …
Fuzzy logic systems for engineering: a tutorial
JM Mendel - Proceedings of the IEEE, 1995 - ieeexplore.ieee.org
A fuzzy logic system (FLS) is unique in that it is able to simultaneously handle numerical
data and linguistic knowledge. It is a nonlinear mapping of an input data (feature) vector into …
data and linguistic knowledge. It is a nonlinear mapping of an input data (feature) vector into …
On combining artificial neural nets
AJC SHARKEY - Connection science, 1996 - Taylor & Francis
This paper reviews research on combining artificial neural nets, and provides an overview
of, and an introduction to, the papers contained in this special issue, and its companion …
of, and an introduction to, the papers contained in this special issue, and its companion …
ATR Japanese speech database as a tool of speech recognition and synthesis
A Kurematsu, K Takeda, Y Sagisaka, S Katagiri… - Speech …, 1990 - Elsevier
A large-scale Japanese speech database has been described. The database basically
consists of (1) a word speech database,(2) a continuous speech database,(3) a database for …
consists of (1) a word speech database,(2) a continuous speech database,(3) a database for …
Modular construction of time-delay neural networks for speech recognition
A Waibel - Neural computation, 1989 - direct.mit.edu
Several strategies are described that overcome limitations of basic network models as steps
towards the design of large connectionist speech recognition systems. The two major areas …
towards the design of large connectionist speech recognition systems. The two major areas …
Multi-class pattern classification using neural networks
G Ou, YL Murphey - Pattern recognition, 2007 - Elsevier
Multi-class pattern classification has many applications including text document
classification, speech recognition, object recognition, etc. Multi-class pattern classification …
classification, speech recognition, object recognition, etc. Multi-class pattern classification …
Efficient classification for multiclass problems using modular neural networks
The rate of convergence of net output error is very low when training feedforward neural
networks for multiclass problems using the backpropagation algorithm. While …
networks for multiclass problems using the backpropagation algorithm. While …
Direct transfer of learned information among neural networks
A touted advantage of symbolic representations is the ease of transferring learned
information from one intelligent agent to another. This paper investigates an analogous …
information from one intelligent agent to another. This paper investigates an analogous …
[图书][B] Speech recognition using neural networks
JM Tebelskis - 1995 - search.proquest.com
This thesis examines how artificial neural networks can benefit a large vocabulary, speaker
independent, continuous speech recognition system. Currently, most speech recognition …
independent, continuous speech recognition system. Currently, most speech recognition …
[图书][B] Subsymbolic natural language processing: An integrated model of scripts, lexicon, and memory
R Miikkulainen - 1993 - books.google.com
Risto Miikkulainen draws on recent connectionist work in language comprehension tocreate
a model that can understand natural language. Using the DISCERN system as an example …
a model that can understand natural language. Using the DISCERN system as an example …