Correlation is one of the most widely used similarity measures in machine learning like Euclidean and Mahalanobis distances. However, compared with proposed numerous discriminant ...
Framework-intensive applications (e.g., Web applications) heavily use temporary data structures, often resulting in performance bottlenecks. This paper presents an optimized blend...
Classification of time series has been attracting great interest over the past decade. Recent empirical evidence has strongly suggested that the simple nearest neighbor algorithm ...
We performed an empirical study exploring people's interactions with an embodied conversational agent (ECA) while performing two tasks. Conditions varied with respect to 1) w...
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...