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CVPR
1999
IEEE
14 years 10 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
CVPR
2010
IEEE
14 years 4 months ago
Sufficient Dimensionality Reduction for Visual Sequence Classification
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...
Alex Shyr, Raquel Urtasun, Michael Jordan
CEC
2010
IEEE
13 years 9 months ago
Improving GP classification performance by injection of decision trees
This paper presents a novel hybrid method combining genetic programming and decision tree learning. The method starts by estimating a benchmark level of reasonable accuracy, based ...
Rikard König, Ulf Johansson, Tuve Löfstr...
MLDM
2007
Springer
14 years 2 months ago
Selection of Experts for the Design of Multiple Biometric Systems
Abstract. In the biometric field, different experts are combined to improve the system reliability, as in many application the performance attained by individual experts (i.e., d...
Roberto Tronci, Giorgio Giacinto, Fabio Roli
ICML
2003
IEEE
14 years 8 months ago
Identifying Predictive Structures in Relational Data Using Multiple Instance Learning
This paper introduces an approach for identifying predictive structures in relational data using the multiple-instance framework. By a predictive structure, we mean a structure th...
Amy McGovern, David Jensen