Mar 21, 2015 · DRESS essentially performs dimensionality reduction from the original string space to a new space. This step is called the mapping step. For ...
This paper focuses on protein and DNA data, and it proposes a novel approximate method method for speeding up range queries under the edit distance that ...
Our method works in a filter-and-refine manner, and its key novelty is a query-sensitive mapping that transforms the original string space to a new string space ...
Sep 18, 2015 · Our experimental evaluation demonstrates that, for higher range values and large query sizes, our method produces significantly lower costs and ...
DRESS: dimensionality reduction for efficient sequence search. Alexios Kotsifakos, Alexandra Stefan, Vassilis Athitsos, Gautam Das, Panagiotis Papapetrou.
In statistics, dimension reduction techniques are a set of processes for reducing the number of random variables by obtaining a set of principal variables.
Mar 21, 2024 · Dimensionality reduction changes the data into a simpler, lower-dimensional space that is easier to work with while keeping its main features.
Missing: DRESS: | Show results with:DRESS:
Feb 16, 2024 · Dimensionality reduction techniques for machine learning refers to the technique of reducing the dimension of a data feature set.
DRESS: Dimensionality Reduction for Efficient Sequence Search. Accepted to the Data Mining and Knowledge Discovery Journal (DAMI), to appear. [ Pre-print ...
Jan 14, 2024 · This article explores several popular methods for dimensionality reduction and analyzes their pros, cons, and potential use cases.
Missing: DRESS: search.