Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dimensionality Reduction using Similarity-induced Embeddings   The vast majority of Dimensionality Reduction (DR) techniques rely on
second-order statistics to define their optimization objective. Even though
this provides adequate results in most cases, it comes with several
shortcomings. The methods require carefully designed regularizers and they are
usually prone to outliers. In this work, a new DR framework, that can directly
model the target distribution using the notion of similarity instead of
distance, is introduced. The proposed framework, called Similarity Embedding
Framework, can overcome the aforementioned limitations and provides a
conceptually simpler way to express optimization targets similar to existing DR
techniques. Deriving a new DR technique using the Similarity Embedding
Framework becomes simply a matter of choosing an appropriate target similarity
matrix. A variety of classical tasks, such as performing supervised
dimensionality reduction and providing out-of-of-sample extensions, as well as,
new novel techniques, such as providing fast linear embeddings for complex
techniques, are demonstrated in this paper using the proposed framework. Six
datasets from a diverse range of domains are used to evaluate the proposed
method and it is demonstrated that it can outperform many existing DR
techniques.

16
The categories of this paper are: stat
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex