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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 8 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
CIKM
2008
Springer
13 years 9 months ago
A latent variable model for query expansion using the hidden markov model
We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed...
Qiang Huang, Dawei Song
RAS
2008
123views more  RAS 2008»
13 years 7 months ago
Fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping
This work investigates the use of semantic information to link ground level occupancy maps and aerial images. A ground level semantic map, which shows open ground and indicates th...
Martin Persson, Tom Duckett, Achim J. Lilienthal
ICPR
2008
IEEE
14 years 8 months ago
A new objective function for sequence labeling
We propose a new loss function for discriminative learning of Markov random fields, which is an intermediate loss function between the sequential loss and the pointwise loss. We s...
Hisashi Kashima, Yuta Tsuboi
ICPR
2004
IEEE
14 years 8 months ago
Fast Object and Pose Recognition Through Minimum Entropy Coding
We present a pattern recognizer to classify a variety of objects and their pose on a table from real world images. Learning of weights in a linear discriminant is based on estimat...
Günter Westphal, Rolf P. Würtz