Masha Naslidnyk

papers

1. Preprint

   Comparing Scale Parameter Estimators for Gaussian Process Regression: Cross Validation and Maximum Likelihood

   Naslidnyk, Masha, Kanagawa, Motonobu, Karvonen, Toni, and Mahsereci, Maren

   arXiv preprint arXiv:2307.07466 2023

   arXiv Bib PDF

   @article{naslidnyk2023comparing,
     title = {Comparing Scale Parameter Estimators for Gaussian Process Regression: Cross Validation and Maximum Likelihood},
     author = {Naslidnyk, Masha and Kanagawa, Motonobu and Karvonen, Toni and Mahsereci, Maren},
     journal = {arXiv preprint arXiv:2307.07466},
     year = {2023},
     pdf = {http://arxiv.org/pdf/2307.07466.pdf},
     arxiv = {2307.07466},
     selected = true,
     abbr = {Preprint},
     bibtex_show = {true}
   }

2. ICML

   Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference

   Bharti, Ayush, Naslidnyk, Masha, Key, Oscar, Kaski, Samuel, and Briol, François-Xavier

   In International Conference on Machine Learning 2023

   arXiv Bib PDF Code

   @inproceedings{bharti2023optimally,
     title = {Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference},
     author = {Bharti, Ayush and Naslidnyk, Masha and Key, Oscar and Kaski, Samuel and Briol, François-Xavier},
     booktitle = {International Conference on Machine Learning},
     year = {2023},
     organization = {PMLR},
     pdf = {http://arxiv.org/pdf/2301.11674.pdf},
     arxiv = {2301.11674},
     selected = true,
     abbr = {ICML},
     code = {http://github.com/bharti-ayush/optimally-weighted_MMD},
     bibtex_show = {true}
   }

3. NeurIPS

   Invariant Priors for Bayesian Quadrature

   Naslidnyk, Masha, Gonzalez, Javier, and Mahsereci, Maren

   In NeurIPS 2021 Workshop. Your Model Is Wrong: Robustness and Misspecification in Probabilistic Modeling 2021

   arXiv Bib PDF

   @inproceedings{naslidnyk2021invariant,
     title = {Invariant Priors for Bayesian Quadrature},
     author = {Naslidnyk, Masha and Gonzalez, Javier and Mahsereci, Maren},
     booktitle = {NeurIPS 2021 Workshop. Your Model Is Wrong: Robustness and Misspecification in Probabilistic Modeling},
     year = {2021},
     pdf = {http://arxiv.org/pdf/2112.01578.pdf},
     arxiv = {2112.01578},
     selected = true,
     abbr = {NeurIPS},
     bibtex_show = {true}
   }

4. EMNLP-IJCNLP

   Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets

   Balkır, Esma, Naslidnyk, Masha, Palfrey, Dave, and Mittal, Arpit

   In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) 2019

   arXiv Bib PDF Code

   @inproceedings{balkir2019using,
     title = {Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets},
     author = {Balk{\i}r, Esma and Naslidnyk, Masha and Palfrey, Dave and Mittal, Arpit},
     booktitle = {Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
     year = {2019},
     selected = true,
     abbr = {EMNLP-IJCNLP},
     pdf = {http://aclanthology.org/D19-1368.pdf},
     arxiv = {1910.11583},
     code = {http://github.com/awslabs/joint_biased_embeddings},
     bibtex_show = {true}
   }

5. NeurIPS

   Improving knowledge graph embeddings with inferred entity types

   Balkır, Esma, Naslidnyk, Masha, Palfrey, Dave, and Mittal, Arpit

   In NeurIPS 2018 Workshop: Relational Representation Learning 2018

   Bib PDF

   @inproceedings{balkir2018improving,
     title = {Improving knowledge graph embeddings with inferred entity types},
     author = {Balk{\i}r, Esma and Naslidnyk, Masha and Palfrey, Dave and Mittal, Arpit},
     booktitle = {NeurIPS 2018 Workshop: Relational Representation Learning},
     year = {2018},
     selected = true,
     abbr = {NeurIPS},
     pdf = {http://assets.amazon.science/e9/3e/22eeb3154040b237bc7b67b6dd3f/improved-knowledge-graph-embeddings-by-using-inferred-entity-types.pdf},
     bibtex_show = {true}
   }