11 citations · 21 across the 11 of their papers we have counts for
13 papers
SGS-GNN: A Supervised Graph Sparsification method for Graph Neural Networks
Siddhartha Shankar Das, Naheed Anjum Arafat, Muftiqur Rahman +3
We propose SGS-GNN, a novel supervised graph sparsifier that learns the sampling probability distribution of edges and samples sparse subgraphs of a user-specified size to reduce t…
Parallel Algorithms for Median Consensus Clustering in Complex Networks
Md Taufique Hussain, Mahantesh Halappanavar, Samrat Chatterjee +3
We develop an algorithm that finds the consensus of many different clustering solutions of a graph. We formulate the problem as a median set partitioning problem and propose a gree…
Approximate Bipartite -Matching using Multiplicative Auction
Bhargav Samineni, S M Ferdous, Mahantesh Halappanavar +1
Given a bipartite graph with vertices and edges and a function , a -matching is a subset of edges such that every verte…
Picasso: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing
S M Ferdous, Reece Neff, Bo Peng +6
A coloring of a graph is an assignment of colors to vertices such that no two neighboring vertices have the same color. The need for memory-efficient coloring algorithms is motivat…
Semi-Supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach
Yu Wang, Yuxuan Yin, Karthik Somayaji Nanjangud Suryanarayana +5
Modeling dynamical systems is crucial for a wide range of tasks, but it remains challenging due to complex nonlinear dynamics, limited observations, or lack of prior knowledge. Rec…
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory
Karthik Somayaji NS, Yu Wang, Malachi Schram +4
Risk-sensitive reinforcement learning (RL) has garnered significant attention in recent years due to the growing interest in deploying RL agents in real-world scenarios. A critical…