by Katharina Dost | Apr 16, 2021 | AI Reading Group, News
New methods for time-to-event prediction are proposed by extending the Cox proportional hazards model with neural networks. Building on methodology from nested case-control studies, we propose a loss function that scales well to large data sets, and enables fitting of...
by Katharina Dost | Apr 15, 2021 | Bias, Fairness, ML Student Seminar, News
Speaker: Annie Lu, PhD student, supervised by Yun Sing Koh, and Joerg Wicker Abstract: Regional varieties of languages such as dialects have proved to have different syntactic and semantic features in the linguistics discipline. However, these dialects have low...
by jkim072 | Apr 12, 2021 | Adversarial Learning, AI Reading Group, Computational Sustainability, News
For many real-world tasks obtaining a complete feature set is prohibitively expensive, especially in healthcare. Specifically, physicians must constantly balance the trade-off between predictive performance and cost for which features to observe. In this paper we...
by Katharina Dost | Mar 25, 2021 | Computational Sustainability, ML Student Seminar, News
Speaker: Nooriyan Poonawala-Lohani, PhD student, supervised by Mehnaz Adnan, Pat Riddle, and Joerg Wicker Abstract: Influenza is a communicable respiratory illness that can cause serious public health hazards. Due to its huge threat to the community, accurate...
by Katharina Dost | Mar 10, 2021 | ML Student Seminar, News
Speaker: Zhenyun Deng, PhD student, supervised by Michael Wittbrock, and Pat Riddle Abstract: Multi-hop question has become an important challenge in reading comprehension (RC) because it requires integrating information from scattered texts across multiple...
