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...
— Most robotic vision algorithms are proposed by envisaging robots operating in structured environments where the world is assumed to be rigid. These algorithms fail to provide o...
Fast retrieval methods are critical for large-scale and
data-driven vision applications. Recent work has explored
ways to embed high-dimensional features or complex distance
fun...
Power minimization under variability is formulated as a rigorous statistical robust optimization program with a guarantee of power and timing yields. Both power and timing metrics...
We study the minimum diameter color-spanning set problem which has recently drawn some attention in the database community. We show that the problem can be solved in polynomial tim...