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» Neural Dynamics with Stochasticity
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NIPS
2008
14 years 11 months ago
Deep Learning with Kernel Regularization for Visual Recognition
In this paper we aim to train deep neural networks for rapid visual recognition. The task is highly challenging, largely due to the lack of a meaningful regularizer on the functio...
Kai Yu, Wei Xu, Yihong Gong
NIPS
2001
14 years 11 months ago
(Not) Bounding the True Error
We present a new approach to bounding the true error rate of a continuous valued classifier based upon PAC-Bayes bounds. The method first constructs a distribution over classifier...
John Langford, Rich Caruana
ICRA
2007
IEEE
117views Robotics» more  ICRA 2007»
15 years 4 months ago
Predicting Object Dynamics from Visual Images through Active Sensing Experiences
Prediction of dynamic features is an important task for determining the manipulation strategies of an object. This paper presents a technique for predicting dynamics of objects re...
Shun Nishide, Tetsuya Ogata, Jun Tani, Kazunori Ko...
NN
1998
Springer
112views Neural Networks» more  NN 1998»
14 years 9 months ago
Continuous attractors and oculomotor control
A recurrent neural network can possess multiple stable states, a property that many brain theories have implicated in learning and memory. There is good evidence for such multista...
H. Sebastian Seung
JCB
2006
185views more  JCB 2006»
14 years 9 months ago
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
Andrew Golightly, Darren J. Wilkinson