5 accepted papers
Aligning egocentric video with wearable sensors has shown promise for human action recognition, but faces practical limitations in user discomfort, privacy concerns, and scalability. We explore exocentric video with ambient sensors as a non-intrusive, scalable alternative. However, the Global Alignm
In social networks, people influence each other through social links, which can be represented as propagation among nodes in graphs. Influence minimization (IMIN) is the problem of manipulating the structures of an input graph (e.g., removing edges) to reduce the propagation among nodes. IMIN can re…
As a neural network's depth increases, it can improve generalization performance. However, training deep networks is challenging due to gradient and signal propagation issues. To address these challenges, extensive theoretical research and various methods have been introduced. Despite these advances…
Conflict is a critical element in the narrative, inciting dramatic tension. This paper introduces CNGCI (Conflict-driven Narrative Generation through Commonsense Inference), a neuro-symbolic framework designed to generate coherent stories embedded with conflict using commonsense inference. Our frame…
The success of a specific neural network architecture is closely tied to the dataset and task it tackles; there is no one-size-fits-all solution. Thus considerable efforts have been made to quickly and accurately estimate the performances of neural architectures without full training or evaluation f…