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ORCIDAhmed Rashed
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2020 – today
- 2024
[j1]Nourhan Ahmed, Ahmed Rashed, Lars Schmidt-Thieme
:
Learning attentive attribute-aware node embeddings in dynamic environments. Int. J. Data Sci. Anal. 17(2): 189-201 (2024)- [c12]Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme:
HMAR: Hierarchical Masked Attention for Multi-behaviour Recommendation. PAKDD (5) 2024: 131-143 - [c11]Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme:
Multi-Behavioral Sequential Recommendation. RecSys 2024: 902-906 - [i7]Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme:
HMAR: Hierarchical Masked Attention for Multi-Behaviour Recommendation. CoRR abs/2405.09638 (2024) - 2023
- [b1]Ahmed Rashed:
Enhanced Item Recommendation with Auxiliary Information. University of Hildesheim, Germany, 2023 - [i6]Mariam Ayman, Youssef El-harty, Ahmed Rashed, Ahmed Fathy, Ahmed Abdullah, Omar Wassim, Walid Gomaa:
BlockCampus: A Blockchain-Based DApp for enhancing Student Engagement and Reward Mechanisms in an Academic Community for E-JUST University. CoRR abs/2307.11662 (2023) - [i5]Shereen Elsayed, Ahmed Rashed, Lars Schmidt-Thieme:
Context-Aware Sequential Model for Multi-Behaviour Recommendation. CoRR abs/2312.09684 (2023) - 2022
- [c10]Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme:
Context and Attribute-Aware Sequential Recommendation via Cross-Attention. RecSys 2022: 71-80 - [i4]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:
A.I. and Data-Driven Mobility at Volkswagen Financial Services AG. CoRR abs/2202.04411 (2022) - [i3]Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme:
CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-Attention. CoRR abs/2204.06519 (2022) - 2021
- [c9]Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme:
A Guided Learning Approach for Item Recommendation via Surrogate Loss Learning. SIGIR 2021: 605-613 - [i2]Shereen Elsayed, Daniela Thyssens, Ahmed Rashed, Lars Schmidt-Thieme, Hadi Samer Jomaa:
Do We Really Need Deep Learning Models for Time Series Forecasting? CoRR abs/2101.02118 (2021) - 2020
- [c8]Ahmed Rashed, Shayan Jawed, Lars Schmidt-Thieme, Andre Hintsches:
MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems. RecSys 2020: 230-239
2010 – 2019
- 2019
- [c7]Shayan Jawed, Ahmed Rashed, Lars Schmidt-Thieme:
Multi-step Forecasting via Multi-task Learning. IEEE BigData 2019: 790-799 - [c6]Luis Alberto Barradas Chacon, Artem Fedoskin, Ekaterina Shcheglakova, Sutthida Neamsup, Ahmed Rashed:
Emotion Analysis Using Heart Rate Data. DEXA Workshops 2019: 147-154 - [c5]Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme:
Weighted Personalized Factorizations for Network Classification with Approximated Relation Weights. ICAART (Revised Selected Papers) 2019: 100-117 - [c4]Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme:
Multi-Label Network Classification via Weighted Personalized Factorizations. ICAART (2) 2019: 357-366 - [c3]Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme:
Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings. KDD 2019: 1132-1140 - [c2]Ahmed Rashed, Shayan Jawed, Jens Rehberg, Josif Grabocka, Lars Schmidt-Thieme, Andre Hintsches:
A Deep Multi-task Approach for Residual Value Forecasting. ECML/PKDD (3) 2019: 467-482 - [c1]Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme:
Attribute-aware non-linear co-embeddings of graph features. RecSys 2019: 314-321 - [i1]Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme:
Multi-Label Network Classification via Weighted Personalized Factorizations. CoRR abs/1902.09294 (2019)
Coauthor Index
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