103 citations · 316 across the 24 of their papers we have counts for
24 papers
Pre-trained Neural Recommenders: A Transferable Zero-Shot Framework for Recommendation Systems
Junting Wang, Adit Krishnan, Hari Sundaram +1
Modern neural collaborative filtering techniques are critical to the success of e-commerce, social media, and content-sharing platforms. However, despite technical advances -- for…
Packet Reception Probability: Packets That You Can't Decode Can Help Keep You Safe
Subham De, Deepak Vasisht, Hari Sundaram +1
This paper provides a robust, scalable Bluetooth Low-Energy (BLE) based indoor localization solution using commodity hardware. While WiFi-based indoor localization has been widely…
Beyond Localized Graph Neural Networks: An Attributed Motif Regularization Framework
Aravind Sankar, Junting Wang, Adit Krishnan +1
We present InfoMotif, a new semi-supervised, motif-regularized, learning framework over graphs. We overcome two key limitations of message passing in popular graph neural networks…
GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation
Aravind Sankar, Yanhong Wu, Yuhang Wu +3
We study the problem of making item recommendations to ephemeral groups, which comprise users with limited or no historical activities together. Existing studies target persistent…
Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation
Adit Krishnan, Mahashweta Das, Mangesh Bendre +2
The rapid proliferation of new users and items on the social web has aggravated the gray-sheep user/long-tail item challenge in recommender systems. Historically, cross-domain co-c…
Discovering Strategic Behaviors for Collaborative Content-Production in Social Networks
Yuxin Xiao, Adit Krishnan, Hari Sundaram
Some social networks provide explicit mechanisms to allocate social rewards such as reputation based on user activity, while the mechanism is more opaque in other networks. Nonethe…