Generate Natural Language Explanations for Recommendation

Current explainable recommendation models mostlygenerate textual explanations based on pre-defined sentence templates . We propose a hierarchical sequence-to-sequence model (HSS) for personalized explanation generation . We further propose an auto-denoisingmechanism based on topical item feature words for sentence generation . This research is one of the initial steps to grant intelligent agents with the ability toexplain itself based on natural language sentences, say the authors of the study .…

Reconfigurable Intelligent Surface Assisted Mobile Edge Computing with Heterogeneous Learning Tasks

Mobile edgecomputing (MEC) provides a natural platform for AI applications since it is with rich computation resources to train machine learning (ML) models, as well as low-latency access to the data generated by mobile and internet of things(IoT) devices . An alternating optimization (AO)-based framework is proposed to optimizethe three terms iteratively, where a successive convex approximation(SCA)-based algorithm is developed to solve the power allocation problem .…

Prediction of High Performance Computing Input Output Variability and Its Application to Optimization for System Configurations

Performance variability is an important measure for a reliable highperformance computing (HPC) system . The prediction of HPC variability is a challenging problem in HPC systems and there is little statistical work on this problem to date . We evaluate performance of themethods by measuring prediction accuracy at previously unseen system configurations .…