Ahmed Rashed

According to our database, Ahmed Rashed authored at least 19 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Learning attentive attribute-aware node embeddings in dynamic environments.

Nourhan Ahmed, Ahmed Rashed, Lars Schmidt-Thieme

Int. J. Data Sci. Anal., March, 2024

Multi-Behavioral Sequential Recommendation.

Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

HMAR: Hierarchical Masked Attention for Multi-behaviour Recommendation.

Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

2023

Enhanced Item Recommendation with Auxiliary Information.

Ahmed Rashed

PhD thesis, 2023

Context-Aware Sequential Model for Multi-Behaviour Recommendation.

Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme

CoRR, 2023

BlockCampus: A Blockchain-Based DApp for enhancing Student Engagement and Reward Mechanisms in an Academic Community for E-JUST University.

Mariam Ayman, Youssef El-harty, Ahmed Rashed, Ahmed Fathy, Ahmed Abdullah, Omar Wassim, Walid Gomaa

CoRR, 2023

2022

CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-Attention.

Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme

CoRR, 2022

A.I. and Data-Driven Mobility at Volkswagen Financial Services AG.

Shayan Jawed, Mofassir ul Islam Arif, Ahmed Rashed, Kiran Madhusudhanan, Shereen Elsayed, Mohsan Jameel, Alexei Volk, Andre Hintsches, Marlies Kornfeld, Katrin Lange, Lars Schmidt-Thieme

CoRR, 2022

Context and Attribute-Aware Sequential Recommendation via Cross-Attention.

Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

2021

Do We Really Need Deep Learning Models for Time Series Forecasting?

Shereen Elsayed, Daniela Thyssens, Ahmed Rashed, Lars Schmidt-Thieme, Hadi Samer Jomaa

CoRR, 2021

A Guided Learning Approach for Item Recommendation via Surrogate Loss Learning.

Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

2020

MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems.

Ahmed Rashed, Shayan Jawed, Lars Schmidt-Thieme, Andre Hintsches

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

2019

Attribute-aware non-linear co-embeddings of graph features.

Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme

Proceedings of the 13th ACM Conference on Recommender Systems, 2019

A Deep Multi-task Approach for Residual Value Forecasting.

Ahmed Rashed, Shayan Jawed, Jens Rehberg, Josif Grabocka, Lars Schmidt-Thieme, Andre Hintsches

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings.

Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Weighted Personalized Factorizations for Network Classification with Approximated Relation Weights.

Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme

Proceedings of the Agents and Artificial Intelligence - 11th International Conference, 2019

Multi-Label Network Classification via Weighted Personalized Factorizations.

Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme

Proceedings of the 11th International Conference on Agents and Artificial Intelligence, 2019

Emotion Analysis Using Heart Rate Data.

Luis Alberto Barradas Chacon, Artem Fedoskin, Ekaterina Shcheglakova, Sutthida Neamsup, Ahmed Rashed

Proceedings of the Database and Expert Systems Applications, 2019

Multi-step Forecasting via Multi-task Learning.

Shayan Jawed, Ahmed Rashed, Lars Schmidt-Thieme

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019