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NIPS
1997
14 years 26 days ago
Hybrid NN/HMM-Based Speech Recognition with a Discriminant Neural Feature Extraction
In thispaper, we present a novelhybridarchitecture forcontinuousspeech recognition systems. It consists of a continuous HMM system extended by an arbitrary neural network that is ...
Daniel Willett, Gerhard Rigoll
NIPS
1997
14 years 26 days ago
Mapping a Manifold of Perceptual Observations
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
Joshua B. Tenenbaum
NIPS
1997
14 years 26 days ago
Minimax and Hamiltonian Dynamics of Excitatory-Inhibitory Networks
A Lyapunov function for excitatory-inhibitory networks is constructed. The construction assumes symmetric interactions within excitatory and inhibitory populations of neurons, and...
H. Sebastian Seung, Tom J. Richardson, J. C. Lagar...
NIPS
1997
14 years 26 days ago
Local Dimensionality Reduction
Stefan Schaal, Sethu Vijayakumar, Christopher G. A...
NIPS
1997
14 years 26 days ago
Intrusion Detection with Neural Networks
With the rapid expansion of computer networks during the past few years, security has become a crucial issue for modern computer systems. A good way to detect illegitimate use is ...
Jake Ryan, Meng-Jang Lin, Risto Miikkulainen
NIPS
1997
14 years 26 days ago
EM Algorithms for PCA and SPCA
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Sam T. Roweis
NIPS
1997
14 years 26 days ago
Just One View: Invariances in Inferotemporal Cell Tuning
In macaque inferotemporal cortex (IT), neurons have been found to respond selectively to complex shapes while showing broad tuning (“invariance”) with respect to stimulus tran...
Maximilian Riesenhuber, Tomaso Poggio
NIPS
1997
14 years 26 days ago
Reinforcement Learning with Hierarchies of Machines
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
Ronald Parr, Stuart J. Russell