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Bibek Paudel
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2020 – today
- 2021
- [j2]Tome Eftimov, Bibek Paudel, Gorjan Popovski, Dragi Kocev:
A Framework for Evaluating Personalized Ranking Systems by Fusing Different Evaluation Measures. Big Data Res. 25: 100211 (2021) - [c10]Daphna Keidar, Mian Zhong, Ce Zhang, Yash Raj Shrestha, Bibek Paudel:
Towards Automatic Bias Detection in Knowledge Graphs. EMNLP (Findings) 2021: 3804-3811 - [c9]Bibek Paudel, Abraham Bernstein:
Random Walks with Erasure: Diversifying Personalized Recommendations on Social and Information Networks. WWW 2021: 2046-2057 - [i8]Bibek Paudel, Abraham Bernstein:
Random Walks with Erasure: Diversifying Personalized Recommendations on Social and Information Networks. CoRR abs/2102.09635 (2021) - [i7]Daphna Keidar, Mian Zhong, Ce Zhang, Yash Raj Shrestha, Bibek Paudel:
Towards Automatic Bias Detection in Knowledge Graphs. CoRR abs/2109.10697 (2021) - 2020
- [i6]Mario Arduini, Lorenzo Noci, Federico Pirovano, Ce Zhang, Yash Raj Shrestha, Bibek Paudel:
Adversarial Learning for Debiasing Knowledge Graph Embeddings. CoRR abs/2006.16309 (2020) - [i5]Leopold Franz, Yash Raj Shrestha, Bibek Paudel:
A Deep Learning Pipeline for Patient Diagnosis Prediction Using Electronic Health Records. CoRR abs/2006.16926 (2020)
2010 – 2019
- 2019
- [c8]Bibek Paudel, Dragi Kocev, Tome Eftimov:
Mix and Rank: A Framework for Benchmarking Recommender Systems. IEEE BigData 2019: 3717-3726 - [c7]Gorjan Popovski, Bibek Paudel, Tome Eftimov, Barbara Korousic-Seljak:
Exploring a standardized language for describing foods using embedding techniques. IEEE BigData 2019: 5172-5176 - [c6]Wen Zhang, Bibek Paudel, Wei Zhang, Abraham Bernstein, Huajun Chen:
Interaction Embeddings for Prediction and Explanation in Knowledge Graphs. WSDM 2019: 96-104 - [c5]Wen Zhang, Bibek Paudel, Liang Wang, Jiaoyan Chen, Hai Zhu, Wei Zhang, Abraham Bernstein, Huajun Chen:
Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning. WWW 2019: 2366-2377 - [i4]Wen Zhang, Bibek Paudel, Wei Zhang, Abraham Bernstein, Huajun Chen:
Interaction Embeddings for Prediction and Explanation in Knowledge Graphs. CoRR abs/1903.04750 (2019) - [i3]Wen Zhang, Bibek Paudel, Liang Wang, Jiaoyan Chen, Hai Zhu, Wei Zhang, Abraham Bernstein, Huajun Chen:
Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning. CoRR abs/1903.08948 (2019) - [i2]Bibek Paudel, Abraham Bernstein:
Cross-Cutting Political Awareness through Diverse News Recommendations. CoRR abs/1909.01495 (2019) - 2018
- [c4]Matthias Baumgartner, Wen Zhang, Bibek Paudel, Daniele Dell'Aglio, Huajun Chen, Abraham Bernstein:
Aligning Knowledge Base and Document Embedding Models Using Regularized Multi-Task Learning. ISWC (1) 2018: 21-37 - [i1]Bibek Paudel, Sandro Luck, Abraham Bernstein:
Loss Aversion in Recommender Systems: Utilizing Negative User Preference to Improve Recommendation Quality. CoRR abs/1812.11422 (2018) - 2017
- [j1]Bibek Paudel, Fabian Christoffel, Chris Newell, Abraham Bernstein:
Updatable, Accurate, Diverse, and Scalable Recommendations for Interactive Applications. ACM Trans. Interact. Intell. Syst. 7(1): 1:1-1:34 (2017) - [c3]Bibek Paudel, Thilo Haas, Abraham Bernstein:
Fewer Flops at the Top: Accuracy, Diversity, and Regularization in Two-Class Collaborative Filtering. RecSys 2017: 215-223 - 2015
- [c2]Fabian Christoffel, Bibek Paudel, Chris Newell, Abraham Bernstein:
Blockbusters and Wallflowers: Accurate, Diverse, and Scalable Recommendations with Random Walks. RecSys 2015: 163-170 - [c1]Philip Stutz, Bibek Paudel, Mihaela Verman, Abraham Bernstein:
Random Walk TripleRush: Asynchronous Graph Querying and Sampling. WWW 2015: 1034-1044
Coauthor Index
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