Kate Smith-Miles

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While recognition of most facial variations, such as identity, expression, and gender, has been extensively studied, automatic age estimation has rarely been explored. In contrast to other facial variations, aging variation presents several unique characteristics which make age estimation a challenging task. This paper proposes an automatic age estimation(More)
The algorithm selection problem [Rice 1976] seeks to answer the question: <i>Which algorithm is likely to perform best for my problem&quest;</i> Recognizing the problem as a learning task in the early 1990's, the machine learning community has developed the field of meta-learning, focused on learning about learning algorithm performance on classification(More)
This paper introduces a new method for learning algorithm evaluation and selection, with empirical results based on classification. The empirical study has been conducted among 8 algorithms/classifiers with 100 different classification problems. We evaluate the algorithms’ performance in terms of a variety of accuracy and complexity measures. Consistent(More)
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is critical for us to find a way to resolve the outstanding problems that make most clustering methods impractical under certain circumstances. When the time series is very long, some(More)
Association rule mining is an active data mining research area. However, most ARM algorithms cater to a centralized environment. In contrast to previous ARM algorithms, we have developed a distributed algorithm, called optimized distributed association mining, for geographically distributed data sets. ODAM generates support counts of candidate itemsets(More)
The continuous growth in the size and use of the Internet is creating difficulties in the search for information. A sophisticated method to organize the layout of the information and assist user navigation is therefore particularly important. In this paper, we evaluate the feasibility of using a self-organizing map (SOM) to mine web log data and provide a(More)
Human age estimation by face images is an interesting yet challenging research topic emerging in recent years. This paper extends our previous work on facial age estimation (a linear method named AGES). In order to match the nonlinear nature of the human aging progress, a new algorithm named KAGES is proposed based on a nonlinear subspace trained on the(More)
For univariate forecasting, there are various statistical models and computational algorithms available. In real-world exercises, too many choices can create difficulties in selecting the most appropriate technique, especially for users lacking sufficient knowledge of forecasting. This paper provides evidence, in the form of an empirical study on(More)