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ORCIDMuhammad Ammad-ud-din
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2020 – today
- 2021
[c4]Farwa K. Khan, Adrian Flanagan, Kuan Eeik Tan, Zareen Alamgir
, Muhammad Ammad-ud-din:
A Payload Optimization Method for Federated Recommender Systems. RecSys 2021: 432-442- [i7]Farwa K. Khan, Adrian Flanagan, Kuan Eeik Tan, Zareen Alamgir, Muhammad Ammad-ud-din:
A Payload Optimization Method for Federated Recommender Systems. CoRR abs/2107.13078 (2021) - 2020
- [c3]Adrian Flanagan, Were Oyomno, Alexander Grigorievskiy, Kuan Eeik Tan, Suleiman A. Khan, Muhammad Ammad-ud-din:
Federated Multi-view Matrix Factorization for Personalized Recommendations. ECML/PKDD (2) 2020: 324-347 - [i6]Adrian Flanagan, Were Oyomno, Alexander Grigorievskiy, Kuan Eeik Tan, Suleiman A. Khan, Muhammad Ammad-ud-din:
Federated Multi-view Matrix Factorization for Personalized Recommendations. CoRR abs/2004.04256 (2020)
2010 – 2019
- 2019
- [i5]Muhammad Ammad-ud-din, Elena Ivannikova, Suleiman A. Khan, Were Oyomno, Qiang Fu, Kuan Eeik Tan, Adrian Flanagan:
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System. CoRR abs/1901.09888 (2019) - 2017
- [b1]Muhammad Ammad-ud-din:
Machine learning methods for improving drug response prediction in cancer. Aalto University, Espoo, Finland, 2017 - [j4]Muhammad Ammad-ud-din, Suleiman A. Khan, Krister Wennerberg, Tero Aittokallio:
Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression. Bioinform. 33(14): i359-i368 (2017) - [j3]Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski:
GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis. J. Mach. Learn. Res. 18: 39:1-39:5 (2017) - [c2]Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski:
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. IUI 2017: 547-552 - 2016
- [j2]Muhammad Ammad-ud-din, Suleiman A. Khan, Disha Malani, Astrid Murumägi, Olli-P. Kallioniemi, Tero Aittokallio, Samuel Kaski:
Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization. Bioinform. 32(17): 455-463 (2016) - [c1]Marta Soare, Muhammad Ammad-ud-din, Samuel Kaski:
Regression with n→1 by Expert Knowledge Elicitation. ICMLA 2016: 734-739 - [i4]Marta Soare, Muhammad Ammad-ud-din, Samuel Kaski:
Regression with n$\to$1 by Expert Knowledge Elicitation. CoRR abs/1605.06477 (2016) - [i3]Muhammad Ammad-ud-din, Suleiman A. Khan, Disha Malani, Astrid Murumägi, Olli-P. Kallioniemi, Tero Aittokallio, Samuel Kaski:
Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization. CoRR abs/1606.03623 (2016) - [i2]Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski:
GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis. CoRR abs/1611.01534 (2016) - [i1]Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski:
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. CoRR abs/1612.02487 (2016) - 2014
- [j1]Muhammad Ammad-ud-din, Elisabeth Georgii, Mehmet Gönen, Tuomo Laitinen, Olli-P. Kallioniemi, Krister Wennerberg, Antti Poso, Samuel Kaski:
Integrative and Personalized QSAR Analysis in Cancer by Kernelized Bayesian Matrix Factorization. J. Chem. Inf. Model. 54(8): 2347-2359 (2014)
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