Browsing by Author "Salehi-Abari, Amirali"

Now showing items 1-6 of 6

    • Enhanced knowledge distillation by auxiliary classifiers 

      Asadian, Aryan (2021-08-01)
      Deep neural models have shown promising results in various areas, e.g., computer vision and natural language processing, at the cost of high computation and storage resource consumption. These characteristics of deep neural ...

    • Group representation learning for group recommendation 

      Sajadi Ghaemmaghami, Sarina (2021-01-01)
      Group recommender systems facilitate group decision making for a set of individuals (e.g., a group of friends, a team, a corporation, etc.). Existing group recommendation methods mostly learn group members' individual ...

    • JoVA-hinge: joint variational autoencoders for personalized recommendation with implicit feedback 

      Askari Firoozjayi, Bahare (2020-12-01)
      Recently, Variational Autoencoders (VAEs) have shown remarkable performance in collaborative filtering (CF) with implicit feedback. These existing recommendation models learn user representations to reconstruct or predict ...

    • Peer evaluation with graph neural networks 

      Namanloo, Alireza A. (2021-12-01)
      Peer assessment systems are rising in various social contexts, such as peer grading in large (online) classrooms, peer review in conferences, peer art evaluation, etc. However, peer assessments might not be as accurate as ...

    • Scalable subgraph representation learning through simplification 

      Louis, Paul (2023-06-01)
      Link prediction on graphs is a fundamental problem. Subgraph representation learning approaches (SGRLs), by transforming link prediction to graph classification on the subgraphs around the links, have achieved state-of-the-art ...

    • Subgraph classification through neighborhood pooling 

      Jacob, Shweta Ann (2023-06-01)
      Subgraph classification is an emerging field in graph representation learning where the task is to classify a group of nodes (i.e., a subgraph) within a graph. Graph neural networks (GNNs) are the de facto solution for ...