activity
20172021
most citedTransfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation

66 citations · 72 across the 4 of their papers we have counts for

collaborators

7 papers

cs.DS2020

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…

cs.IR202066 cited

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…

cs.SI2020

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…

cs.SI2020

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…

cs.SI20192 cited

An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms

Kanika Narang, Chaoqi Yang, Adit Krishnan +3

This paper addresses the question of identifying the best candidate answer to a question on Community Question Answer (CQA) forums. The problem is important because Individuals oft…

cs.DS2019

Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension

Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan +1

Spectral functions of large matrices contains important structural information about the underlying data, and is thus becoming increasingly important. Many times, large matrices re…