Liudmila Ostroumova

According to our database, Liudmila Ostroumova authored at least 60 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of two.

2024

Measuring Diversity: Axioms and Challenges.

Mikhail Mironov, Liudmila Prokhorenkova

CoRR, 2024

Challenges of Generating Structurally Diverse Graphs.

Fedor Velikonivtsev, Mikhail Mironov, Liudmila Prokhorenkova

CoRR, 2024

TabGraphs: A Benchmark and Strong Baselines for Learning on Graphs with Tabular Node Features.

Gleb Bazhenov, Oleg Platonov, Liudmila Prokhorenkova

CoRR, 2024

Discrete Neural Algorithmic Reasoning.

Gleb Rodionov, Liudmila Prokhorenkova

CoRR, 2024

2023

Neural Algorithmic Reasoning Without Intermediate Supervision.

Gleb Rodionov, Liudmila Prokhorenkova

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond.

Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts.

Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Which Tricks are Important for Learning to Rank?

Ivan Lyzhin, Aleksei Ustimenko, Andrey Gulin, Liudmila Prokhorenkova

Proceedings of the International Conference on Machine Learning, 2023

Gradient Boosting Performs Gaussian Process Inference.

Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

When Less Is More: Systematic Analysis of Cascade-Based Community Detection.

Liudmila Prokhorenkova, Alexey Tikhonov, Nelly Litvak

ACM Trans. Knowl. Discov. Data, 2022

Characterizing Graph Datasets for Node Classification: Beyond Homophily-Heterophily Dichotomy.

Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova

CoRR, 2022

Gradient Boosting Performs Low-Rank Gaussian Process Inference.

Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova

CoRR, 2022

Good Classification Measures and How to Find Them.

Martijn Gösgens, Anton Zhiyanov, Alexey Tikhonov, Liudmila Prokhorenkova

CoRR, 2022

Graph-based Nearest Neighbor Search in Hyperbolic Spaces.

Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks.

Andrey Malinin, Neil Band, Alexander Ganshin, German Chesnokov, Yarin Gal, Mark J. F. Gales, Alexey Noskov, Andrey Ploskonosov, Liudmila Prokhorenkova, Ivan Provilkov, Vatsal Raina, Vyas Raina, Mariya Shmatova, Panos Tigas, Boris Yangel

CoRR, 2021

Overlapping Spaces for Compact Graph Representations.

Kirill Shevkunov, Liudmila Prokhorenkova

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks.

Andrey Malinin, Neil Band, Yarin Gal, Mark J. F. Gales, Alexander Ganshin, German Chesnokov, Alexey Noskov, Andrey Ploskonosov, Liudmila Prokhorenkova, Ivan Provilkov, Vatsal Raina, Vyas Raina, Denis Roginskiy, Mariya Shmatova, Panagiotis Tigas, Boris Yangel

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Good Classification Measures and How to Find Them.

Martijn Gösgens, Anton Zhiyanov, Aleksey Tikhonov, Liudmila Prokhorenkova

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SGLB: Stochastic Gradient Langevin Boosting.

Aleksei Ustimenko, Liudmila Prokhorenkova

Proceedings of the 38th International Conference on Machine Learning, 2021

Systematic Analysis of Cluster Similarity Indices: How to Validate Validation Measures.

Martijn Gösgens, Alexey Tikhonov, Liudmila Prokhorenkova

Proceedings of the 38th International Conference on Machine Learning, 2021

Uncertainty in Gradient Boosting via Ensembles.

Andrey Malinin, Liudmila Prokhorenkova, Aleksei Ustimenko

Proceedings of the 9th International Conference on Learning Representations, 2021

Boost then Convolve: Gradient Boosting Meets Graph Neural Networks.

Sergei Ivanov, Liudmila Prokhorenkova

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Overlaying Spaces and Practical Applicability of Complex Geometries.

Kirill Shevkunov, Liudmila Prokhorenkova

CoRR, 2020

Global Graph Curvature.

Liudmila Prokhorenkova, Egor Samosvat, Pim van der Hoorn

Proceedings of the Algorithms and Models for the Web Graph - 17th International Workshop, 2020

StochasticRank: Global Optimization of Scale-Free Discrete Functions.

Aleksei Ustimenko, Liudmila Prokhorenkova

Proceedings of the 37th International Conference on Machine Learning, 2020

Graph-based Nearest Neighbor Search: From Practice to Theory.

Liudmila Prokhorenkova, Aleksandr Shekhovtsov

Proceedings of the 37th International Conference on Machine Learning, 2020

Embedding Words in Non-Vector Space with Unsupervised Graph Learning.

Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

Systematic Analysis of Cluster Similarity Indices: Towards Bias-free Cluster Validation.

Martijn Gösgens, Liudmila Prokhorenkova, Alexey Tikhonov

CoRR, 2019

Graph-based Nearest Neighbor Search: From Practice to Theory.

Liudmila Prokhorenkova

CoRR, 2019

Learning Clusters through Information Diffusion.

Liudmila Ostroumova Prokhorenkova, Alexey Tikhonov, Nelly Litvak

Proceedings of the World Wide Web Conference, 2019

Community Detection through Likelihood Optimization: In Search of a Sound Model.

Liudmila Ostroumova Prokhorenkova, Alexey Tikhonov

Proceedings of the World Wide Web Conference, 2019

Using Synthetic Networks for Parameter Tuning in Community Detection.

Liudmila Prokhorenkova

Proceedings of the Algorithms and Models for the Web Graph - 16th International Workshop, 2019

A Statistical Test of Heterogeneous Subgraph Densities to Assess Clusterability.

Pierre Miasnikof, Liudmila Prokhorenkova, Alexander Y. Shestopaloff, Andrei M. Raigorodskii

Proceedings of the Learning and Intelligent Optimization - 13th International Conference, 2019

2018

Preferential placement for community structure formation.

Liudmila Ostroumova Prokhorenkova, Egor Samosvat, Aleksandr Dorodnykh

Internet Math., 2018

Clustering Properties of Spatial Preferential Attachment Model.

Lenar Iskhakov, Bogumil Kaminski, Maksim Mironov, Pawel Pralat, Liudmila Ostroumova Prokhorenkova

Proceedings of the Algorithms and Models for the Web Graph - 15th International Workshop, 2018

CatBoost: unbiased boosting with categorical features.

Liudmila Ostroumova Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

General results on preferential attachment and clustering coefficient.

Liudmila Ostroumova Prokhorenkova

Optim. Lett., 2017

Assortativity in Generalized Preferential Attachment Models.

Liudmila Ostroumova Prokhorenkova, Alexander M. Krot

Internet Math., 2017

Local Clustering Coefficient in Generalized Preferential Attachment Models.

Alexander M. Krot, Liudmila Ostroumova Prokhorenkova

Internet Math., 2017

Modularity in several random graph models.

Liudmila Ostroumova Prokhorenkova, Pawel Pralat, Andrei M. Raigorodskii

Electron. Notes Discret. Math., 2017

Fighting biases with dynamic boosting.

Anna Veronika Dorogush, Andrey Gulin, Gleb Gusev, Nikita Kazeev, Liudmila Ostroumova Prokhorenkova, Aleksandr Vorobev

CoRR, 2017

2016

Global Clustering Coefficient in Scale-Free Weighted and Unweighted Networks.

Liudmila Ostroumova Prokhorenkova

Internet Math., 2016

Recency-based preferential attachment models.

Liudmila Ostroumova Prokhorenkova, Egor Samosvat

J. Complex Networks, 2016

Publication Date Prediction through Reverse Engineering of the Web.

Liudmila Ostroumova Prokhorenkova, Petr Prokhorenkov, Egor Samosvat, Pavel Serdyukov

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

Modularity of Complex Networks Models.

Liudmila Ostroumova Prokhorenkova, Pawel Pralat, Andrei M. Raigorodskii

Proceedings of the Algorithms and Models for the Web Graph - 13th International Workshop, 2016

2015

What can be Found on the Web and How: A Characterization of Web Browsing Patterns.

Alexey Tikhonov, Liudmila Ostroumova Prokhorenkova, Arseniy Chelnokov, Ivan Bogatyy, Gleb Gusev

Proceedings of the ACM Web Science Conference, 2015

PageRank in Undirected Random Graphs.

Konstantin Avrachenkov, Arun Kadavankandy, Liudmila Ostroumova Prokhorenkova, Andrei M. Raigorodskii

Proceedings of the Algorithms and Models for the Web Graph - 12th International Workshop, 2015

Adaptive Caching of Fresh Web Search Results.

Liudmila Ostroumova Prokhorenkova, Yury Ustinovskiy, Egor Samosvat, Damien Lefortier, Pavel Serdyukov

Proceedings of the Advances in Information Retrieval, 2015

2014

Global Clustering Coefficient in Scale-Free Networks.

Liudmila Ostroumova Prokhorenkova, Egor Samosvat

Proceedings of the Algorithms and Models for the Web Graph - 11th International Workshop, 2014

Quick Detection of High-Degree Entities in Large Directed Networks.

Konstantin Avrachenkov, Nelly Litvak, Liudmila Ostroumova Prokhorenkova, Eugenia Suyargulova

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Crawling Policies Based on Web Page Popularity Prediction.

Liudmila Ostroumova, Ivan Bogatyy, Arseniy Chelnokov, Alexey Tikhonov, Gleb Gusev

Proceedings of the Advances in Information Retrieval, 2014

2013

The Distribution of Second Degrees in the Buckley-Osthus Random Graph Model.

Andrey Kupavskii, Liudmila Ostroumova, Dmitry A. Shabanov, Prasad Tetali

Internet Math., 2013

Generalized Preferential Attachment: Tunable Power-Law Degree Distribution and Clustering Coefficient.

Liudmila Ostroumova, Alexander Ryabchenko, Egor Samosvat

Proceedings of the Algorithms and Models for the Web Graph - 10th International Workshop, 2013

Evolution of the Media Web.

Damien Lefortier, Liudmila Ostroumova, Egor Samosvat

Proceedings of the Algorithms and Models for the Web Graph - 10th International Workshop, 2013

Studying page life patterns in dynamical web.

Alexey Tikhonov, Ivan Bogatyy, Pavel Burangulov, Liudmila Ostroumova, Vitaliy Koshelev, Gleb Gusev

Proceedings of the 36th International ACM SIGIR conference on research and development in Information Retrieval, 2013

Timely crawling of high-quality ephemeral new content.

Damien Lefortier, Liudmila Ostroumova, Egor Samosvat, Pavel Serdyukov

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012

A Model of the Fresh Internet

Damien Lefortier, Liudmila Ostroumova, Egor Samosvat

CoRR, 2012

Empirical validation of the buckley-osthus model for the web host graph: degree and edge distributions.

Maxim Zhukovskiy, Dmitry Vinogradov, Yuri Pritykin, Liudmila Ostroumova, Evgeny Grechnikov, Gleb Gusev, Pavel Serdyukov, Andrei M. Raigorodskii

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

Prediction of retweet cascade size over time.

Andrey Kupavskii, Liudmila Ostroumova, Alexey Umnov, Svyatoslav Usachev, Pavel Serdyukov, Gleb Gusev, Andrey Kustarev

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012