… transformation is sufficient and we only need to do the Fourier transform on a subset of … ǫ
and a query set S ⊂ [n] of size k, we propose an algorithm to compute an approximate Fourier …

… that affect the search time of a proximity query, if we assume the CPU time to be negligible;
… In section 4.4 we develop algorithms for efficiently processing similarity queries using an R-…

… on a data set, we describe a fast query processing algorithm that uses the index to filter out
… We have chosen the first k Fourier coefficient of a time series as our features. The reason for …

… This is a plot of thequery time bound we obtained and the p-stable LSHthat has query …
points from all queries, we learnedthe best parameters for our algorithm, requestingthe same …

… query model, in which the Fourier transform algorithm is set. In order to keep the algorithm
run-time … coefficients, 2n, calculating this hypothesis would take exponential time, while our …

… We present a query processing algorithm that uses the underlying multidimensional index
built … Since we use the Fourier series representation of time series data as our features, and a …

… an algorithm due to Kushilevitz and Mansour[16] can be used to weakly learn DNF using
membership queries in polynomial time, … DNF expressions in polynomial time in any nontrivial …

… This algorithm compares favorably to [l 11 which requires time quadratic in n to achieve …
tially close functions typically require exponentially many queries to the function's values. Thus …

… the frequency domain instead of time domain. Thanks to the merit of fast Fourier transform,
we … distance directly, which avoids performing timeconsuming alignment between sequences. …

… time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT)
to map time … DFT is the existence of a fast algorithm, the Fast Fourier Transform (FFT), that …