—A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach,...
Michal Lewandowski, Jesus Martinez-Del-Rincon, Dim...
Existing work on similar sequence matching has focused on either whole matching or range subsequence matching. In this paper, we present novel methods for ranked subsequence match...
In a public cloud, bandwidth is traditionally priced in a pay-asyou-go model. Reflecting the recent trend of augmenting cloud computing with bandwidth guarantees, we consider a n...
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...
Abstract. We present a new method for proving lower bounds in evolutionary computation based on fitness-level arguments and an additional condition on transition probabilities bet...