5 papers
Upper-Linearizability of Online Non-Monotone DR-Submodular Maximization over Down-Closed Convex Sets
Yiyang Lu, Haresh Jadav, Mohammad Pedramfar +2
We study online maximization of non-monotone Diminishing-Return(DR)-submodular functions over down-closed convex sets, a regime where existing projection-free online methods suffer…
Stronger Approximation Guarantees for Non-Monotone γ-Weakly DR-Submodular Maximization
Hareshkumar Jadav, Ranveer Singh, Vaneet Aggarwal
Maximizing submodular objectives under constraints is a fundamental problem in machine learning and optimization. We study the maximization of a nonnegative, non-monotone -weak…
Cartesian Prime Graphs and Cospectral Families
Abhinav Bitragunta, Hareshkumar Jadav, Ranveer Singh
We introduce a method for constructing larger families of connected cospectral graphs from two given cospectral families of sizes and . The resulting family size depends on…
Strengthening Wilf's lower bound on clique number
Hareshkumar Jadav, Sreekara Madyastha, Rahul Raut +1
Given an integer , deciding whether a graph has a clique of size is an NP-complete problem. Wilf's inequality provides a spectral bound for the clique number of simple graph…
A Hybrid Similarity-Aware Graph Neural Network with Transformer for Node Classification
Aman Singh, Shahid Shafi Dar, Ranveer Singh +1
Node classification has gained significant importance in graph deep learning with real-world applications such as recommendation systems, drug discovery, and citation networks. Gra…