SeerNet at SemEval-2018 Task 1: Domain Adaptation for Affect in Tweets

The paper describes the best performing system for the SemEval-2018 Affect in Tweets (English) sub-tasks. The system focuses on the ordinal classification and regression sub-tasks for valence and emotion. For ordinal classification valence is classified into 7 different classes ranging from -3 to 3 whereas emotion is classified into 4 different classes 0 to 3 separately for each emotion namely anger, fear, joy and sadness. The regression sub-tasks estimate the intensity of valence and each emotion. The system performs domain adaptation of 4 different models and creates an ensemble to give the final prediction. The proposed system achieved 1st position out of 75 teams which participated in the fore-mentioned sub-tasks. We outperform the baseline model by margins ranging from 49.2% to 76.4%, thus, pushing the state-of-the-art significantly.Comment: SemEval-2018 Task 1: Affect in Tweet

UCI and Entrepreneurship, Blog 3

Student blog posts from the Great VCU Bike Race Book

Amalgam Fillings: Do Dental Patients Have a Right to Informed Consent

Recent animal studies have shown significant mercury absorption from dental fillings and resulted in unfavorable media attention. Yet, an FDA advisory committee has found no evidence of Risk to dental patients, and many dentists believe that patients are being unnecessarily alarmed. The paper reviews the history of amalgam fillings through the recent animal studies and concludes that the Risk, whatever it may prove to be, is sufficiently high to warrant permitting patients to choose between amalgam and alternative dental filling materials