Relevance feedback (RF) is an iterative process, which refines the retrievals by utilizing the user's feedback on previously retrieved results. Traditional RF techniques solel...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
Information extraction (IE) systems are costly to build because they require development texts, parsing tools, and specialized dictionaries for each application domain and each na...
This paper presents a novel learning method for human action detection in video sequences. The detecting problem is not limited in controlled settings like stationary background or...
Multiarmed bandit problem is a typical example of a dilemma between exploration and exploitation in reinforcement learning. This problem is expressed as a model of a gambler playi...
We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunki...