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Ahad N. Zehmakan

8 accepted papers

2026

Adaptive Initial Residual Connections for GNNs with Theoretical Guarantees

AAAI 2026technical

Message passing is the core operation in graph neural networks, where each node updates its embeddings by aggregating information from its neighbors. However, in deep architectures, this process often leads to diminished expressiveness. A popular solution is the use of residual connections, where th

Cited by 0SourcePDFScholar
2026

Beyond Fixed Depth: Adaptive Graph Neural Networks for Node Classification Under Varying Homophily

AAAI 2026technical

Graph Neural Networks (GNNs) have achieved significant success in addressing node classification tasks. However, the effectiveness of traditional GNNs degrades on heterophilic graphs, where connected nodes often belong to different labels or properties. While recent work has introduced mechanisms to

Cited by 0SourcePDFScholar
2025

DeepSN: A Sheaf Neural Framework for Influence Maximization

AAAI 2025technical

Influence maximization is a key topic in data mining, with broad applications in social network analysis and viral marketing. In recent years, researchers have increasingly turned to machine learning techniques to address this problem. By learning the underlying diffusion processes from data, these…

2023

Why Rumors Spread Fast in Social Networks, and How to Stop It

IJCAI 2023poster

We study a rumor spreading model where individuals are connected via a network structure. Initially, only a small subset of the individuals are spreading a rumor. Each individual who is connected to a spreader, starts spreading the rumor with some probability as a function of their trust in the spre…

2022

On the Oracle Complexity of Higher-Order Smooth Non-Convex Finite-Sum Optimization

AISTATS 2022poster

We prove lower bounds for higher-order methods in smooth non-convex finite-sum optimization. Our contribution is threefold: We first show that a deterministic algorithm cannot profit from the finite-sum structure of the objective and that simulating a pth-order regularized method on the whole functi…

Cited by 2SourcePDFScholar
2021

Majority Vote in Social Networks: Make Random Friends or Be Stubborn to Overpower Elites

IJCAI 2021poster

Consider a graph G, representing a social network. Assume that initially each node is colored either black or white, which corresponds to a positive or negative opinion regarding a consumer product or a technological innovation. In the majority model, in each round all nodes simultaneously update th…

Cited by 16SourcePDFScholar