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» Learning Complex and Sparse Events in Long Sequences
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CORR
2010
Springer
127views Education» more  CORR 2010»
13 years 6 months ago
Learning Networks of Stochastic Differential Equations
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
José Bento, Morteza Ibrahimi, Andrea Montan...
ICML
2006
IEEE
14 years 8 months ago
Regression with the optimised combination technique
We consider the sparse grid combination technique for regression, which we regard as a problem of function reconstruction in some given function space. We use a regularised least ...
Jochen Garcke
JMLR
2002
133views more  JMLR 2002»
13 years 7 months ago
Learning Precise Timing with LSTM Recurrent Networks
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
Felix A. Gers, Nicol N. Schraudolph, Jürgen S...
ICMCS
2006
IEEE
153views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Learning-Based Interactive Video Retrieval System
This paper presents an interactive video event retrieval system based on improved adaboost learning. This system consists of three main steps. Firstly, a long video sequence is pa...
Chi-Jiunn Wu, Hui-Chi Zeng, Szu-Hao Huang, Shang-H...
JMLR
2008
151views more  JMLR 2008»
13 years 7 months ago
Learning to Combine Motor Primitives Via Greedy Additive Regression
The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
Manu Chhabra, Robert A. Jacobs