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ORCIDLiudmila Ostroumova
Liudmila Ostroumova Prokhorenkova – Liudmila Prokhorenkova
Person information
- affiliation: Moscow Institute of Physics and Technology, Russia
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2020 – today
- 2024
[i31]Gleb Rodionov, Liudmila Prokhorenkova:
Discrete Neural Algorithmic Reasoning. CoRR abs/2402.11628 (2024)- 2023
- [c41]Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova:
A critical look at the evaluation of GNNs under heterophily: Are we really making progress? ICLR 2023 - [c40]Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova:
Gradient Boosting Performs Gaussian Process Inference. ICLR 2023 - [c39]Ivan Lyzhin, Aleksei Ustimenko, Andrey Gulin, Liudmila Prokhorenkova:
Which Tricks are Important for Learning to Rank? ICML 2023: 23264-23278 - [c38]Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova:
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts. NeurIPS 2023 - [c37]Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova:
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond. NeurIPS 2023 - [c36]Gleb Rodionov, Liudmila Prokhorenkova:
Neural Algorithmic Reasoning Without Intermediate Supervision. NeurIPS 2023 - [i30]Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova:
A critical look at the evaluation of GNNs under heterophily: are we really making progress? CoRR abs/2302.11640 (2023) - [i29]Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova:
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts. CoRR abs/2302.13875 (2023) - [i28]Gleb Rodionov, Liudmila Prokhorenkova:
Neural Algorithmic Reasoning Without Intermediate Supervision. CoRR abs/2306.13411 (2023) - 2022
- [j9]Liudmila Prokhorenkova
, Alexey Tikhonov, Nelly Litvak:
When Less Is More: Systematic Analysis of Cascade-Based Community Detection. ACM Trans. Knowl. Discov. Data 16(4): 78:1-78:22 (2022) - [c35]Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov:
Graph-based Nearest Neighbor Search in Hyperbolic Spaces. ICLR 2022 - [i27]Martijn Gösgens, Anton Zhiyanov, Alexey Tikhonov, Liudmila Prokhorenkova:
Good Classification Measures and How to Find Them. CoRR abs/2201.09044 (2022) - [i26]Ivan Lyzhin, Aleksei Ustimenko, Andrey Gulin, Liudmila Prokhorenkova:
Which Tricks are Important for Learning to Rank? CoRR abs/2204.01500 (2022) - [i25]Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova:
Gradient Boosting Performs Low-Rank Gaussian Process Inference. CoRR abs/2206.05608 (2022) - [i24]Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova:
Characterizing Graph Datasets for Node Classification: Beyond Homophily-Heterophily Dichotomy. CoRR abs/2209.06177 (2022) - 2021
- [c34]Sergei Ivanov, Liudmila Prokhorenkova:
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks. ICLR 2021 - [c33]Andrey Malinin, Liudmila Prokhorenkova, Aleksei Ustimenko:
Uncertainty in Gradient Boosting via Ensembles. ICLR 2021 - [c32]Martijn Gösgens, Alexey Tikhonov, Liudmila Prokhorenkova:
Systematic Analysis of Cluster Similarity Indices: How to Validate Validation Measures. ICML 2021: 3799-3808 - [c31]Aleksei Ustimenko, Liudmila Prokhorenkova:
SGLB: Stochastic Gradient Langevin Boosting. ICML 2021: 10487-10496 - [c30]Martijn Gösgens, Anton Zhiyanov, Aleksey Tikhonov, Liudmila Prokhorenkova:
Good Classification Measures and How to Find Them. NeurIPS 2021: 17136-17147 - [c29]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:
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks. NeurIPS Datasets and Benchmarks 2021 - [c28]Kirill Shevkunov, Liudmila Prokhorenkova:
Overlapping Spaces for Compact Graph Representations. NeurIPS 2021: 11665-11677 - [i23]Sergei Ivanov, Liudmila Prokhorenkova:
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks. CoRR abs/2101.08543 (2021) - [i22]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:
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks. CoRR abs/2107.07455 (2021) - 2020
- [c27]Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita:
Embedding Words in Non-Vector Space with Unsupervised Graph Learning. EMNLP (1) 2020: 7317-7331 - [c26]Liudmila Prokhorenkova, Aleksandr Shekhovtsov:
Graph-based Nearest Neighbor Search: From Practice to Theory. ICML 2020: 7803-7813 - [c25]Aleksei Ustimenko, Liudmila Prokhorenkova:
StochasticRank: Global Optimization of Scale-Free Discrete Functions. ICML 2020: 9669-9679 - [c24]Liudmila Prokhorenkova, Egor Samosvat, Pim van der Hoorn:
Global Graph Curvature. WAW 2020: 16-35 - [i21]Aleksei Ustimenko, Liudmila Prokhorenkova:
SGLB: Stochastic Gradient Langevin Boosting. CoRR abs/2001.07248 (2020) - [i20]Liudmila Prokhorenkova, Alexey Tikhonov, Nelly Litvak:
When Less is More: Systematic Analysis of Cascade-based Community Detection. CoRR abs/2002.00840 (2020) - [i19]Aleksei Ustimenko, Liudmila Prokhorenkova:
StochasticRank: Global Optimization of Scale-Free Discrete Functions. CoRR abs/2003.02122 (2020) - [i18]Aleksei Ustimenko, Liudmila Prokhorenkova, Andrey Malinin:
Uncertainty in Gradient Boosting via Ensembles. CoRR abs/2006.10562 (2020) - [i17]Kirill Shevkunov, Liudmila Prokhorenkova:
Overlaying Spaces and Practical Applicability of Complex Geometries. CoRR abs/2007.02445 (2020) - [i16]Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita:
Embedding Words in Non-Vector Space with Unsupervised Graph Learning. CoRR abs/2010.02598 (2020)
2010 – 2019
- 2019
- [c23]Pierre Miasnikof, Liudmila Prokhorenkova, Alexander Y. Shestopaloff, Andrei M. Raigorodskii:
A Statistical Test of Heterogeneous Subgraph Densities to Assess Clusterability. LION 2019: 17-29 - [c22]Liudmila Prokhorenkova:
Using Synthetic Networks for Parameter Tuning in Community Detection. WAW 2019: 1-15 - [c21]Liudmila Ostroumova Prokhorenkova, Alexey Tikhonov:
Community Detection through Likelihood Optimization: In Search of a Sound Model. WWW 2019: 1498-1508 - [c20]Liudmila Ostroumova Prokhorenkova, Alexey Tikhonov, Nelly Litvak:
Learning Clusters through Information Diffusion. WWW 2019: 3151-3157 - [i15]Liudmila Ostroumova Prokhorenkova:
Using synthetic networks for parameter tuning in community detection. CoRR abs/1906.04555 (2019) - [i14]Liudmila Prokhorenkova:
Graph-based Nearest Neighbor Search: From Practice to Theory. CoRR abs/1907.00845 (2019) - [i13]Martijn Gösgens, Liudmila Prokhorenkova, Alexey Tikhonov:
Systematic Analysis of Cluster Similarity Indices: Towards Bias-free Cluster Validation. CoRR abs/1911.04773 (2019) - 2018
- [j8]Liudmila Ostroumova Prokhorenkova, Egor Samosvat, Aleksandr Dorodnykh:
Preferential placement for community structure formation. Internet Math. 2018 (2018) - [c19]Liudmila Ostroumova Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin:
CatBoost: unbiased boosting with categorical features. NeurIPS 2018: 6639-6649 - [c18]Lenar Iskhakov, Bogumil Kaminski, Maksim Mironov, Pawel Pralat, Liudmila Ostroumova Prokhorenkova:
Clustering Properties of Spatial Preferential Attachment Model. WAW 2018: 30-43 - [i12]Liudmila Ostroumova Prokhorenkova, Alexey Tikhonov:
Community detection through likelihood optimization: in search of a sound model. CoRR abs/1802.04472 (2018) - [i11]Lenar Iskhakov, Bogumil Kaminski, Maksim Mironov, Liudmila Ostroumova Prokhorenkova, Pawel Pralat:
Clustering Properties of Spatial Preferential Attachment Model. CoRR abs/1802.05127 (2018) - 2017
- [j7]Liudmila Ostroumova Prokhorenkova, Pawel Pralat, Andrei M. Raigorodskii:
Modularity in several random graph models. Electron. Notes Discret. Math. 61: 947-953 (2017) - [j6]Alexander M. Krot, Liudmila Ostroumova Prokhorenkova:
Local Clustering Coefficient in Generalized Preferential Attachment Models. Internet Math. 2017 (2017) - [j5]Liudmila Ostroumova Prokhorenkova, Alexander M. Krot:
Assortativity in Generalized Preferential Attachment Models. Internet Math. 2017 (2017) - [j4]Liudmila Ostroumova Prokhorenkova:
General results on preferential attachment and clustering coefficient. Optim. Lett. 11(2): 279-298 (2017) - [c17]Aleksandr Dorodnykh, Liudmila Ostroumova Prokhorenkova, Egor Samosvat:
Preferential Placement for Community Structure Formation. WAW 2017: 75-89 - [i10]Aleksandr Dorodnykh, Liudmila Ostroumova Prokhorenkova, Egor Samosvat:
Preferential placement for community structure formation. CoRR abs/1706.05655 (2017) - [i9]Anna Veronika Dorogush, Andrey Gulin, Gleb Gusev, Nikita Kazeev, Liudmila Ostroumova Prokhorenkova, Aleksandr Vorobev:
Fighting biases with dynamic boosting. CoRR abs/1706.09516 (2017) - 2016
- [j3]Liudmila Ostroumova Prokhorenkova, Egor Samosvat:
Recency-based preferential attachment models. J. Complex Networks 4(4): 475-499 (2016) - [j2]Liudmila Ostroumova Prokhorenkova:
Global Clustering Coefficient in Scale-Free Weighted and Unweighted Networks. Internet Math. 12(1-2): 54-67 (2016) - [c16]Alexander M. Krot, Liudmila Ostroumova Prokhorenkova:
Assortativity in Generalized Preferential Attachment Models. WAW 2016: 9-21 - [c15]Liudmila Ostroumova Prokhorenkova, Pawel Pralat, Andrei M. Raigorodskii:
Modularity of Complex Networks Models. WAW 2016: 115-126 - [c14]Liudmila Ostroumova Prokhorenkova, Petr Prokhorenkov, Egor Samosvat, Pavel Serdyukov:
Publication Date Prediction through Reverse Engineering of the Web. WSDM 2016: 123-132 - 2015
- [c13]Liudmila Ostroumova Prokhorenkova, Yury Ustinovskiy, Egor Samosvat, Damien Lefortier, Pavel Serdyukov:
Adaptive Caching of Fresh Web Search Results. ECIR 2015: 110-122 - [c12]Alexander M. Krot, Liudmila Ostroumova Prokhorenkova:
Local Clustering Coefficient in Generalized Preferential Attachment Models. WAW 2015: 15-28 - [c11]Konstantin Avrachenkov, Arun Kadavankandy, Liudmila Ostroumova Prokhorenkova, Andrei M. Raigorodskii:
PageRank in Undirected Random Graphs. WAW 2015: 151-163 - [c10]Alexey Tikhonov, Liudmila Ostroumova Prokhorenkova, Arseniy Chelnokov, Ivan Bogatyy, Gleb Gusev:
What can be Found on the Web and How: A Characterization of Web Browsing Patterns. WebSci 2015: 14:1-14:10 - [i8]Liudmila Ostroumova Prokhorenkova:
Global clustering coefficient in scale-free weighted and unweighted networks. CoRR abs/1507.00925 (2015) - [i7]Arun Kadavankandy, Konstantin Avrachenkov, Liudmila Ostroumova Prokhorenkova, Andrei M. Raigorodskii:
PageRank in undirected random graphs. CoRR abs/1511.04925 (2015) - 2014
- [c9]Liudmila Ostroumova, Ivan Bogatyy, Arseniy Chelnokov, Alexey Tikhonov, Gleb Gusev:
Crawling Policies Based on Web Page Popularity Prediction. ECIR 2014: 100-111 - [c8]Konstantin Avrachenkov, Nelly Litvak, Liudmila Ostroumova Prokhorenkova, Eugenia Suyargulova:
Quick Detection of High-Degree Entities in Large Directed Networks. ICDM 2014: 20-29 - [c7]Liudmila Ostroumova Prokhorenkova, Egor Samosvat:
Global Clustering Coefficient in Scale-Free Networks. WAW 2014: 47-58 - [i6]Konstantin Avrachenkov, Nelly Litvak, Liudmila Ostroumova Prokhorenkova, Eugenia Suyargulova:
Quick Detection of High-degree Entities in Large Directed Networks. CoRR abs/1410.0571 (2014) - 2013
- [j1]Andrey Kupavskii, Liudmila Ostroumova, Dmitry A. Shabanov, Prasad Tetali:
The Distribution of Second Degrees in the Buckley-Osthus Random Graph Model. Internet Math. 9(4): 297-335 (2013) - [c6]Damien Lefortier, Liudmila Ostroumova, Egor Samosvat, Pavel Serdyukov:
Timely crawling of high-quality ephemeral new content. CIKM 2013: 745-750 - [c5]Alexey Tikhonov, Ivan Bogatyy, Pavel Burangulov, Liudmila Ostroumova, Vitaliy Koshelev, Gleb Gusev:
Studying page life patterns in dynamical web. SIGIR 2013: 905-908 - [c4]Damien Lefortier, Liudmila Ostroumova, Egor Samosvat:
Evolution of the Media Web. WAW 2013: 80-92 - [c3]Liudmila Ostroumova, Alexander Ryabchenko, Egor Samosvat:
Generalized Preferential Attachment: Tunable Power-Law Degree Distribution and Clustering Coefficient. WAW 2013: 185-202 - [i5]Andrey Kupavskii, Liudmila Ostroumova, Dmitry A. Shabanov, Prasad Tetali:
The distribution of second degrees in the Buckley-Osthus random graph model. CoRR abs/1304.5715 (2013) - [i4]Damien Lefortier, Liudmila Ostroumova, Egor Samosvat, Pavel Serdyukov:
Timely crawling of high-quality ephemeral new content. CoRR abs/1307.6080 (2013) - 2012
- [c2]Maxim Zhukovskiy, Dmitry Vinogradov, Yuri Pritykin, Liudmila Ostroumova, Evgeny Grechnikov, Gleb Gusev, Pavel Serdyukov, Andrei M. Raigorodskii:
Empirical validation of the buckley-osthus model for the web host graph: degree and edge distributions. CIKM 2012: 1577-1581 - [c1]Andrey Kupavskii, Liudmila Ostroumova, Alexey Umnov, Svyatoslav Usachev, Pavel Serdyukov, Gleb Gusev, Andrey Kustarev:
Prediction of retweet cascade size over time. CIKM 2012: 2335-2338 - [i3]Liudmila Ostroumova, Alexander Ryabchenko, Egor Samosvat:
Generalized preferential attachment: tunable power-law degree distribution and clustering coefficient. CoRR abs/1205.3015 (2012) - [i2]Maxim Zhukovskiy, Dmitry Vinogradov, Yuri Pritykin, Liudmila Ostroumova, Evgeny Grechnikov, Gleb Gusev, Pavel Serdyukov, Andrei M. Raigorodskii:
Empirical Validation of the Buckley--Osthus Model for the Web Host Graph: Degree and Edge Distributions. CoRR abs/1208.2355 (2012) - [i1]Damien Lefortier, Liudmila Ostroumova, Egor Samosvat:
A Model of the Fresh Internet. CoRR abs/1209.4523 (2012)
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