66 citations · 72 across the 6 of their papers we have counts for
6 papers · 1 filter
Near-Optimal Entrywise Sampling of Numerically Sparse Matrices
Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan +1
Many real-world data sets are sparse or almost sparse. One method to measure this for a matrix is the \emph{numerical sparsity}, denoted $\mathsf{ns}(…
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…
Competitively Pricing Parking in a Tree
Max Bender, Jacob Gilbert, Aditya Krishnan +1
Motivated by demand-responsive parking pricing systems we consider posted-price algorithms for the online metrical matching problem and the online metrical searching problem in a t…
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…
Inf-VAE: A Variational Autoencoder Framework to Integrate Homophily and Influence in Diffusion Prediction
Aravind Sankar, Xinyang Zhang, Adit Krishnan +1
Recent years have witnessed tremendous interest in understanding and predicting information spread on social media platforms such as Twitter, Facebook, etc. Existing diffusion pred…