Search Results for author: Sina Sajadmanesh

Found 7 papers, 4 papers with code

GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation

no code implementations2 Mar 2022 Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet, Daniel Gatica-Perez

Graph Neural Networks (GNNs) are powerful models designed for graph data that learn node representation by recursively aggregating information from each node's local neighborhood.

Locally Private Graph Neural Networks

1 code implementation9 Jun 2020 Sina Sajadmanesh, Daniel Gatica-Perez

In this paper, we study the problem of node data privacy, where graph nodes have potentially sensitive data that is kept private, but they could be beneficial for a central server for training a GNN over the graph.

Federated Learning Node Classification +1

Continuous-Time Relationship Prediction in Dynamic Heterogeneous Information Networks

1 code implementation30 Sep 2017 Sina Sajadmanesh, Sogol Bazargani, Jiawei Zhang, Hamid R. Rabiee

In this paper, we try to solve the problem of continuous-time relationship prediction in dynamic and heterogeneous information networks.

Link Prediction

NPGLM: A Non-Parametric Method for Temporal Link Prediction

no code implementations21 Jun 2017 Sina Sajadmanesh, Jiawei Zhang, Hamid R. Rabiee

In this paper, we try to solve the problem of temporal link prediction in information networks.

Link Prediction

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics

1 code implementation8 Mar 2017 Seyed Ali Osia, Ali Shahin Shamsabadi, Sina Sajadmanesh, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi

To this end, instead of performing the whole operation on the cloud, we let an IoT device to run the initial layers of the neural network, and then send the output to the cloud to feed the remaining layers and produce the final result.

Kissing Cuisines: Exploring Worldwide Culinary Habits on the Web

no code implementations26 Oct 2016 Sina Sajadmanesh, Sina Jafarzadeh, Seyed Ali Osia, Hamid R. Rabiee, Hamed Haddadi, Yelena Mejova, Mirco Musolesi, Emiliano De Cristofaro, Gianluca Stringhini

In this paper, we present a large-scale study of recipes published on the web and their content, aiming to understand cuisines and culinary habits around the world.

Predicting Anchor Links between Heterogeneous Social Networks

1 code implementation IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2016 Sina Sajadmanesh, Hamid R. Rabiee, Ali Khodadadi

Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new inter-network link (called anchor link) is formed between the source and target networks.

Social and Information Networks Physics and Society

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