@InProceedings{meisheri-dey:2018:S18-1,
  author    = {Meisheri, Hardik  and  Dey, Lipika},
  title     = {TCS Research at SemEval-2018 Task 1: Learning Robust Representations using Multi-Attention Architecture},
  booktitle = {Proceedings of The 12th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {291--299},
  abstract  = {This paper presents system description of our submission to the SemEval-2018 task-1: Affect in tweets for the English language. We combine three different features generated using deep learning models and traditional methods in support vector machines to create a unified ensemble system. A robust representation of a tweet is learned using a multi-attention based architecture which uses a mixture of different pre-trained embeddings. In addition to this analysis of different features is also presented. Our system ranked 2nd, 5th, and 7th in different subtasks among 75 teams.},
  url       = {http://www.aclweb.org/anthology/S18-1043}
}