Shahar Z Kovalsky — accepted AI-conference papers

2025

Differentiation Through Black-Box Quadratic Programming Solvers

Connor W. Magoon, Fengyu Yang, Noam Aigerman, Shahar Z. Kovalsky

NeurIPS 2025poster

Differentiable optimization has attracted significant research interest, particularly for quadratic programming (QP). Existing approaches for differentiating the solution of a QP with respect to its defining parameters often rely on specific integrated solvers. This integration limits their applicab…

Cited by 0 Source ↗code ↗Scholar ↗

2023

Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals

Tingting Dan, Jiaqi Ding, Ziquan Wei, Shahar Z Kovalsky, Minjeong Kim, Won Hwa Kim +1

NeurIPS 2023poster

Graphs are ubiquitous in various domains, such as social networks and biological systems. Despite the great successes of graph neural networks (GNNs) in modeling and analyzing complex graph data, the inductive bias of locality assumption, which involves exchanging information only within neighboring…

Cited by 3 Source ↗PDF ↗code ↗Scholar ↗