Cyberbullying ends here: Towards robust detection of cyberbullying in social media
The potentially detrimental effects of cyberbullying have led to the development of numerous
automated, data-driven approaches, with emphasis on classification accuracy …
automated, data-driven approaches, with emphasis on classification accuracy …
Stochastic expectation maximization with variance reduction
Expectation-Maximization (EM) is a popular tool for learning latent variable models, but the
vanilla batch EM does not scale to large data sets because the whole data set is needed at …
vanilla batch EM does not scale to large data sets because the whole data set is needed at …
Scalable inference for logistic-normal topic models
Logistic-normal topic models can effectively discover correlation structures among latent
topics. However, their inference remains a challenge because of the non-conjugacy …
topics. However, their inference remains a challenge because of the non-conjugacy …
Integrating topic and latent factors for scalable personalized review-based rating prediction
Personalized review-based rating prediction, a newly emerged research problem, aims at
inferring users' ratings over their unrated items using existing reviews and corresponding …
inferring users' ratings over their unrated items using existing reviews and corresponding …
Sparsemax and relaxed wasserstein for topic sparsity
Topic sparsity refers to the observation that individual documents usually focus on several
salient topics instead of covering a wide variety of topics, and a real topic adopts a narrow …
salient topics instead of covering a wide variety of topics, and a real topic adopts a narrow …
Dynamic, incremental, and continuous detection of cyberbullying in online social media
The potentially detrimental effects of cyberbullying have led to the development of numerous
automated, data-driven approaches, with emphasis on classification accuracy …
automated, data-driven approaches, with emphasis on classification accuracy …
Dynamic online HDP model for discovering evolutionary topics from Chinese social texts
User-generated content such as online reviews in social media evolve rapidly over time. To
better understand the social media content, users not only want to examine what the topics …
better understand the social media content, users not only want to examine what the topics …
[BOOK][B] Machine learning and knowledge discovery in databases
HBK Kersting, SNF Železný - 2013 - Springer
These are the proceedings of the 2013 edition of the European Conference on Machine
Learning and Principles and Practice of Knowledge Discovery in Databases, or ECML …
Learning and Principles and Practice of Knowledge Discovery in Databases, or ECML …
Elastic responding machine for dialog generation with dynamically mechanism selecting
Neural models aiming at generating meaningful and diverse response is attracting
increasing attention over recent years. For a given post, the conventional encoder-decoder …
increasing attention over recent years. For a given post, the conventional encoder-decoder …
Sparse multi-modal topical coding for image annotation
Image annotation plays a significant role in large scale image understanding, indexing and
retrieval. The Probability Topic Models (PTMs) attempt to address this issue by learning …
retrieval. The Probability Topic Models (PTMs) attempt to address this issue by learning …