5 citations · 7 across the 5 of their papers we have counts for
5 papers
Learning User Representations in Online Social Networks using Temporal Dynamics of Information Diffusion
Harvineet Singh, Amitabha Bagchi, Parag Singla
This article presents a novel approach for learning low-dimensional distributed representations of users in online social networks. Existing methods rely on the network structure f…
Non-Count Symmetries in Boolean & Multi-Valued Prob. Graphical Models
Ankit Anand, Ritesh Noothigattu, Parag Singla +1
Lifted inference algorithms commonly exploit symmetries in a probabilistic graphical model (PGM) for efficient inference. However, existing algorithms for Boolean-valued domains ca…
Coarse-to-Fine Lifted MAP Inference in Computer Vision
Haroun Habeeb, Ankit Anand, Mausam +1
There is a vast body of theoretical research on lifted inference in probabilistic graphical models (PGMs). However, few demonstrations exist where lifting is applied in conjunction…
Lifted Region-Based Belief Propagation
David Smith, Parag Singla, Vibhav Gogate
Due to the intractable nature of exact lifted inference, research has recently focused on the discovery of accurate and efficient approximate inference algorithms in Statistical Re…
Contextual Symmetries in Probabilistic Graphical Models
Ankit Anand, Aditya Grover, Mausam +1
An important approach for efficient inference in probabilistic graphical models exploits symmetries among objects in the domain. Symmetric variables (states) are collapsed into met…