Search Results for author:
Found 6 papers, 1 papers with code
Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds
In this work, we investigate whether crowd wisdom is useful in predicting such outcomes and whether their opinions are influenced by the experts in the field.
Transparency and Explanation in Deep Reinforcement Learning Neural Networks
For those systems to be accepted and trusted, the users should be able to understand the reasoning process of the system, i. e. the system should be transparent.
Object-sensitive Deep Reinforcement Learning
In this paper, we propose a novel method that can incorporate object recognition processing to deep reinforcement learning models.
Joint Embedding of Hierarchical Categories and Entities for Concept Categorization and Dataless Classification
Due to the lack of structured knowledge applied in learning distributed representation of cate- gories, existing work cannot incorporate category hierarchies into entity information.
Joint Embeddings of Hierarchical Categories and Entities
Due to the lack of structured knowledge applied in learning distributed representation of categories, existing work cannot incorporate category hierarchies into entity information.~We propose a framework that embeds entities and categories into a semantic space by integrating structured knowledge and taxonomy hierarchy from large knowledge bases.
Machine Comprehension Based on Learning to Rank
Machine comprehension plays an essential role in NLP and has been widely explored with dataset like MCTest.
