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ISNN
2011
Springer
13 years 2 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
ICANN
2011
Springer
13 years 3 months ago
Probabilistic Proactive Timeline Browser
We have developed a browser suitable for finding events from timelines, in particular from life logs and other timelines containing a familiar narrative. The system infers the rel...
Antti Ajanki, Samuel Kaski
ICANN
2011
Springer
13 years 3 months ago
Hybrid Parallel Classifiers for Semantic Subspace Learning
Subspace learning is very important in today's world of information overload. Distinguishing between categories within a subset of a large data repository such as the web and ...
Nandita Tripathi, Michael P. Oakes, Stefan Wermter
ICANN
2011
Springer
13 years 3 months ago
Temperature Prediction in Electric Arc Furnace with Neural Network Tree
Abstract. This paper presents a neural network tree regression system with dynamic optimization of input variable transformations and post-training optimization. The decision tree ...
Miroslaw Kordos, Marcin Blachnik, Tadeusz Wieczore...
ICANN
2011
Springer
13 years 3 months ago
Robot Trajectory Prediction and Recognition Based on a Computational Mirror Neurons Model
Mirror neurons are premotor neurons that are considered to play a role in goal-directed actions, action understanding and even social cognition. As one of the promising research ar...
Junpei Zhong, Cornelius Weber, Stefan Wermter
ICANN
2011
Springer
13 years 3 months ago
Person Tracking Based on a Hybrid Neural Probabilistic Model
This article presents a novel approach for a real-time person tracking system based on particle filters that use different visual streams. Due to the difficulty of detecting a pe...
Wenjie Yan, Cornelius Weber, Stefan Wermter
ICANN
2011
Springer
13 years 3 months ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes
ICANN
2011
Springer
13 years 3 months ago
Bias of Importance Measures for Multi-valued Attributes and Solutions
Attribute importance measures for supervised learning are important for improving both learning accuracy and interpretability. However, it is well-known there could be bias when th...
Houtao Deng, George C. Runger, Eugene Tuv
ICANN
2011
Springer
13 years 3 months ago
Learning Curves for Gaussian Processes via Numerical Cubature Integration
This paper is concerned with estimation of learning curves for Gaussian process regression with multidimensional numerical integration. We propose an approach where the recursion e...
Simo Särkkä
ICANN
2011
Springer
13 years 3 months ago
Transforming Auto-Encoders
The artificial neural networks that are used to recognize shapes typically use one or more layers of learned feature detectors that produce scalar outputs. By contrast, the comput...
Geoffrey E. Hinton, Alex Krizhevsky, Sida D. Wang