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Topic Models

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Conversational Structure Aware and Context Sensitive Topic Model for Online Discussions

6 Feb 2020

Millions of online discussions are generated everyday on social media platforms.

TOPIC MODELS

Optimal estimation of sparse topic models

22 Jan 2020

We derive a finite sample upper bound for our estimator, and show that it matches the minimax lower bound in many scenarios.

DIMENSIONALITY REDUCTION TOPIC MODELS

Random-walk Based Generative Model for Classifying Document Networks

21 Jan 2020

However, existing generative models do not make full use of network structures because they are largely dependent on topic modeling of documents.

TOPIC MODELS

VSEC-LDA: Boosting Topic Modeling with Embedded Vocabulary Selection

15 Jan 2020

When applying a topic model, a relatively standard pre-processing step is to first build a vocabulary of frequent words.

TOPIC MODELS

Topic Extraction of Crawled Documents Collection using Correlated Topic Model in MapReduce Framework

6 Jan 2020

From the evaluation, the proposed approach has a comparable performance in terms of topic coherences with LDA implemented in MapReduce framework.

TOPIC MODELS

Best feature performance in codeswitched hate speech texts

ICLR 2020

How well can hate speech concept be abstracted in order to inform automatic classification in codeswitched texts by machine learning classifiers?

TOPIC MODELS

Discovering Topics With Neural Topic Models Built From PLSA Loss

ICLR 2020

The proposed model uses documents, words, and topics lookup table embedding as neural network model parameters to build probabilities of words given topics, and probabilities of topics given documents.

DOCUMENT EMBEDDING TOPIC MODELS

Precision-Recall Balanced Topic Modelling

NeurIPS 2019

Topic models are becoming increasingly relevant probabilistic models for dimensionality reduction of text data, inferring topics that capture meaningful themes of frequently co-occurring terms.

DIMENSIONALITY REDUCTION INFORMATION RETRIEVAL TOPIC MODELS

Discriminative Topic Modeling with Logistic LDA

NeurIPS 2019

Although it is a discriminative model, we show that logistic LDA can learn from unlabeled data in an unsupervised manner by exploiting the group structure present in the data.

TOPIC MODELS