3 papers
cs.LG2020
Reward Shaping for Human Learning via Inverse Reinforcement Learning
Mark A. Rucker, Layne T. Watson, Matthew S. Gerber +1
Humans are spectacular reinforcement learners, constantly learning from and adjusting to experience and feedback. Unfortunately, this doesn't necessarily mean humans are fast learn…
cs.HC2018
Cluster-based Approach to Improve Affect Recognition from Passively Sensed Data
Mawulolo K. Ameko, Lihua Cai, Mehdi Boukhechba +5
Negative affect is a proxy for mental health in adults. By being able to predict participants' negative affect states unobtrusively, researchers and clinicians will be better posit…
cs.LG2017
HDLTex: Hierarchical Deep Learning for Text Classification
Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa +3
The continually increasing number of documents produced each year necessitates ever improving information processing methods for searching, retrieving, and organizing text. Central…