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ECAI
2004
Springer
15 years 3 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
ACSW
2004
14 years 11 months ago
Learning Dynamics of Pesticide Abuse through Data Mining
Recent studies by agriculture researchers in Pakistan have shown that attempts of crop yield maximization through pro-pesticide state policies have led to a dangerously high pesti...
Ahsan Abdullah, Stephen Brobst, Ijaz Pervaiz
NAACL
1994
14 years 11 months ago
Learning from Relevant Documents in Large Scale Routing Retrieval
The normal practice of selecting relevant documents for training routing queries is to either use all relevants or the 'best n' of them after a (retrieval) ranking opera...
K. L. Kwok, Laszlo Grunfeld
CVPR
2011
IEEE
14 years 5 months ago
Learning Temporally Consistent Rigidities
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...
Jean-Sebastien Franco, Edmond Boyer
INTERSPEECH
2010
14 years 4 months ago
Learning from human errors: prediction of phoneme confusions based on modified ASR training
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...
Bernd T. Meyer, Birger Kollmeier