The Multiple-Orientability Thresholds for Random Hypergraphs† N Fountoulakis, M Khosla, K Panagiotou Combinatorics, Probability and Computing 25 (6), 870-908, 2016 | 38 | 2016 |
The multiple-orientability thresholds for random hypergraphs N Fountoulakis, M Khosla, K Panagiotou Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete …, 2011 | 38* | 2011 |
Macroscopic quantum information processing using spin coherent states T Byrnes, D Rosseau, M Khosla, A Pyrkov, A Thomasen, T Mukai, ... Optics Communications 337, 102-109, 2015 | 34 | 2015 |
Balls into Bins made Faster M Khosla Proceedings of the Twenty-First Annual European Symposium on Algorithms, 601 …, 2013 | 20 | 2013 |
A Comparative Study for Unsupervised Network Representation Learning Methods M Khosla, A Anand, V Setty IEEE Transactions on Knowledge and Data Engineering, 2019 | 16* | 2019 |
Node Representation Learning for Directed Graphs M Khosla, J Leonhardt, W Nejdl, A Anand In ECML 2019, 2019 | 16 | 2019 |
Message Passing Algorithms M Khosla Master Thesis, 2009 | 7 | 2009 |
User Fairness in Recommender Systems J Leonhardt, A Anand, M Khosla Companion Proceedings of the The Web Conference 2018, 2018 | 6 | 2018 |
Delusive PageRank in Incomplete Graphs H Holzmann, A Anand, M Khosla In Complex Networks 2018, 2018 | 6 | 2018 |
A Faster Algorithm for Cuckoo Insertion and Bipartite Matching in Large Graphs M Khosla, A Anand Algorithmica, 1-18, 2019 | 3 | 2019 |
Finding Interpretable Concept Spaces in Node Embeddings using Knowledge Bases M Idahl, M Khosla, A Anand In workshop on Advances in Interpretable Machine Learning and Artificial …, 2019 | 2 | 2019 |
Asynchronous Training of Word Embeddings for Large Text Corpora A Anand, M Khosla, J Singh, JH Zab, Z Zhang In Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019 | 2 | 2019 |
Estimating PageRank deviations in crawled graphs H Holzmann, A Anand, M Khosla Applied Network Science 4 (1), 1-22, 2019 | 1 | 2019 |
What the HAK? Estimating Ranking Deviations in Incomplete Graphs H Holzmann, A Anand, M Khosla Proceedings of the 14th International Workshop on Mining and Learning with …, 2018 | 1 | 2018 |
Valid Explanations for Learning to Rank Models J Singh, M Khosla, A Anand arXiv preprint arXiv:2004.13972, 2020 | | 2020 |
Deep Reinforcement Learning with Graph-based State Representations V Waradpande, D Kudenko, M Khosla arXiv preprint arXiv:2004.13965, 2020 | | 2020 |
Boilerplate Removal using a Neural Sequence Labeling Model J Leonhardt, A Anand, M Khosla Companion Proceedings of the Web Conference 2020, 226-229, 2020 | | 2020 |
Revisiting Feature Selection with Data Complexity NT Dong, M Khosla Proceedings of the 20th IEEE International Conference on Bioinformatics and …, 2020 | | 2020 |
Graph-based State Representation for Deep Reinforcement Learning V Waradpande, D Kudenko, M Khosla In Proceedings of 16th International Workshop on Mining and Learning with …, 2020 | | 2020 |
A consistent evaluation of miRNA-disease association prediction models TNN Dong, M Khosla bioRxiv, 2020 | | 2020 |