Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Continuous-time Infinite Dynamic Topic Models   Topic models are probabilistic models for discovering topical themes in
collections of documents. In real world applications, these models provide us
with the means of organizing what would otherwise be unstructured collections.
They can help us cluster a huge collection into different topics or find a
subset of the collection that resembles the topical theme found in an article
at hand.
  The first wave of topic models developed were able to discover the prevailing
topics in a big collection of documents spanning a period of time. It was later
realized that these time-invariant models were not capable of modeling 1) the
time varying number of topics they discover and 2) the time changing structure
of these topics. Few models were developed to address this two deficiencies.
The online-hierarchical Dirichlet process models the documents with a time
varying number of topics. It varies the structure of the topics over time as
well. However, it relies on document order, not timestamps to evolve the model
over time. The continuous-time dynamic topic model evolves topic structure in
continuous-time. However, it uses a fixed number of topics over time.
  In this dissertation, I present a model, the continuous-time infinite dynamic
topic model, that combines the advantages of these two models 1) the
online-hierarchical Dirichlet process, and 2) the continuous-time dynamic topic
model. More specifically, the model I present is a probabilistic topic model
that does the following: 1) it changes the number of topics over continuous
time, and 2) it changes the topic structure over continuous-time.
  I compared the model I developed with the two other models with different
setting values. The results obtained were favorable to my model and showed the
need for having a model that has a continuous-time varying number of topics and
topic structure.

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The categories of this paper are: nlin
3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph