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ORCIDNikolaj Tatti
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- affiliation: Aalto University, Finland
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2020 – today
- 2024
[j38]Nikolaj Tatti:
Explainable decomposition of nested dense subgraphs. Data Min. Knowl. Discov. 38(6): 3621-3642 (2024)- [j37]Iiro Kumpulainen
, Nikolaj Tatti:
Dense subgraphs induced by edge labels. Mach. Learn. 113(4): 1967-1987 (2024) - [j36]Chamalee Wickrama Arachchi, Nikolaj Tatti:
Recurrent segmentation meets block models in temporal networks. Mach. Learn. 113(8): 5623-5653 (2024) - [j35]Chamalee Wickrama Arachchi, Nikolaj Tatti:
Jaccard-constrained dense subgraph discovery. Mach. Learn. 113(9): 7103-7125 (2024) - [c51]Iiro Kumpulainen, Florian Adriaens, Nikolaj Tatti:
Max-Min Diversification with Asymmetric Distances. KDD 2024: 1440-1450 - [c50]Chamalee Wickrama Arachchi, Iiro Kumpulainen, Nikolaj Tatti:
Dense Subgraph Discovery Meets Strong Triadic Closure. KDD 2024: 3334-3344 - [c49]Chamalee Wickrama Arachchi, Nikolaj Tatti:
Fair Densest Subgraph Across Multiple Graphs. ECML/PKDD (5) 2024: 3-19 - [i58]Atsushi Miyauchi, Florian Adriaens, Francesco Bonchi, Nikolaj Tatti:
Multilayer Correlation Clustering. CoRR abs/2404.16676 (2024) - [i57]Florian Adriaens, Iiro Kumpulainen, Nikolaj Tatti:
Improved Hardness Results of the Cardinality-Based Minimum s-t Cut Problem in Hypergraphs. CoRR abs/2409.07201 (2024) - [i56]Iiro Kumpulainen, Sebastian Dalleiger, Jilles Vreeken, Nikolaj Tatti:
From your Block to our Block: How to Find Shared Structure between Stochastic Block Models over Multiple Graphs. CoRR abs/2412.15476 (2024) - 2023
- [j34]Nikolaj Tatti:
Column-coherent matrix decomposition. Data Min. Knowl. Discov. 37(6): 2564-2588 (2023) - [j33]Nikolaj Tatti:
Fast computation of distance-generalized cores using sampling. Knowl. Inf. Syst. 65(6): 2429-2453 (2023) - [c48]Chamalee Wickrama Arachchi, Nikolaj Tatti:
Jaccard-Constrained Dense Subgraph Discovery. DS 2023: 508-522 - [c47]Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Finding Favourite Tuples on Data Streams with Provably Few Comparisons. KDD 2023: 3229-3238 - [c46]Iiro Kumpulainen, Nikolaj Tatti:
Finding Coherent Node Groups in Directed Graphs. PKDD/ECML Workshops (3) 2023: 486-497 - [c45]Chamalee Wickrama Arachchi, Nikolaj Tatti:
Node ranking in labeled networks. SDM 2023: 415-423 - [c44]Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Ranking with submodular functions on the fly. SDM 2023: 604-612 - [i55]Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Ranking with submodular functions on the fly. CoRR abs/2301.06787 (2023) - [i54]Nikolaj Tatti:
Fast likelihood-based change point detection. CoRR abs/2301.08892 (2023) - [i53]Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Finding Favourite Tuples on Data Streams with Provably Few Comparisons. CoRR abs/2307.02946 (2023) - [i52]Chamalee Wickrama Arachchi, Nikolaj Tatti:
Jaccard-constrained dense subgraph discovery. CoRR abs/2308.15936 (2023) - [i51]Iiro Kumpulainen, Nikolaj Tatti:
Finding coherent node groups in directed graphs. CoRR abs/2310.02993 (2023) - 2022
- [j32]Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Ranking with submodular functions on a budget. Data Min. Knowl. Discov. 36(3): 1197-1218 (2022) - [j31]Nikolaj Tatti:
Maintaining AUC and H-measure over time. Mach. Learn. 111(8): 2839-2862 (2022) - [c43]Chamalee Wickrama Arachchi, Nikolaj Tatti:
Recurrent Segmentation Meets Block Models in Temporal Networks. DS 2022: 445-459 - [c42]Iiro Kumpulainen, Nikolaj Tatti:
Community Detection in Edge-Labeled Graphs. DS 2022: 460-475 - [c41]Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Coresets remembered and items forgotten: submodular maximization with deletions. ICDM 2022: 676-685 - [i50]Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Optimal deletion-robust coreset for submodular maximization. CoRR abs/2203.01241 (2022) - [i49]Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Ranking with submodular functions on a budget. CoRR abs/2204.04168 (2022) - [i48]Chamalee Wickrama Arachchi, Nikolaj Tatti:
Recurrent segmentation meets block models in temporal networks. CoRR abs/2205.09862 (2022) - [i47]Iiro Kumpulainen, Nikolaj Tatti:
Community detection in edge-labeled graphs. CoRR abs/2210.10583 (2022) - 2021
- [j30]Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
The network-untangling problem: from interactions to activity timelines. Data Min. Knowl. Discov. 35(1): 213-247 (2021) - [c40]Nikolaj Tatti:
Fast computation of distance-generalized cores using sampling. ICDM 2021: 609-618 - [c39]Nikolaj Tatti:
Approximation Algorithms for Confidence Bands for Time Series. ECML/PKDD (1) 2021: 437-452 - [i46]Nikolaj Tatti:
Fast computation of distance-generalized cores using sampling. CoRR abs/2112.06154 (2021) - [i45]Nikolaj Tatti:
Maintaining AUC and H-measure over time. CoRR abs/2112.06160 (2021) - [i44]Nikolaj Tatti:
Approximation algorithms for confidence bands for time series. CoRR abs/2112.06225 (2021) - 2020
- [j29]Polina Rozenshtein, Francesco Bonchi, Aristides Gionis, Mauro Sozio, Nikolaj Tatti:
Finding events in temporal networks: segmentation meets densest subgraph discovery. Knowl. Inf. Syst. 62(4): 1611-1639 (2020) - [i43]Sami Hanhijärvi, Markus Ojala, Niko Vuokko, Kai Puolamäki, Nikolaj Tatti, Heikki Mannila:
Tell Me Something I Don't Know: Randomization Strategies for Iterative Data Mining. CoRR abs/2006.09467 (2020) - [i42]Nikolaj Tatti, Hannes Heikinheimo:
Decomposable Families of Itemsets. CoRR abs/2006.09533 (2020)
2010 – 2019
- 2019
- [j28]Nikolaj Tatti:
Strongly polynomial efficient approximation scheme for segmentation. Inf. Process. Lett. 142: 1-8 (2019) - [j27]Nikolaj Tatti:
Density-Friendly Graph Decomposition. ACM Trans. Knowl. Discov. Data 13(5): 54:1-54:29 (2019) - [c38]Nikolaj Tatti:
Fast Likelihood-Based Change Point Detection. ECML/PKDD (1) 2019: 662-677 - [c37]Nikolaj Tatti, Pauli Miettinen:
Boolean matrix factorization meets consecutive ones property. SDM 2019: 729-737 - [i41]Nikolaj Tatti, Pauli Miettinen:
Boolean matrix factorization meets consecutive ones property. CoRR abs/1901.05797 (2019) - [i40]Nikolaj Tatti:
Efficient estimation of AUC in a sliding window. CoRR abs/1902.00632 (2019) - [i39]Nikolaj Tatti:
Computational Complexity of Queries Based on Itemsets. CoRR abs/1902.00633 (2019) - [i38]Nikolaj Tatti:
Itemsets for Real-valued Datasets. CoRR abs/1902.00804 (2019) - [i37]Nikolaj Tatti:
Ranking Episodes using a Partition Model. CoRR abs/1902.01002 (2019) - [i36]Nikolaj Tatti:
Safe projections of binary data sets. CoRR abs/1902.01331 (2019) - [i35]Nikolaj Tatti:
Distances between Data Sets Based on Summary Statistics. CoRR abs/1902.01334 (2019) - [i34]Nikolaj Tatti:
Faster way to agony: Discovering hierarchies in directed graphs. CoRR abs/1902.01477 (2019) - [i33]Nikolaj Tatti, Taneli Mielikäinen, Aristides Gionis, Heikki Mannila:
What is the dimension of your binary data? CoRR abs/1902.01480 (2019) - [i32]Nikolaj Tatti, Aristides Gionis:
Discovering Nested Communities. CoRR abs/1902.01483 (2019) - [i31]Nikolaj Tatti:
Discovering bursts revisited: guaranteed optimization of the model parameters. CoRR abs/1902.01727 (2019) - [i30]Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
Inferring the strength of social ties: a community-driven approach. CoRR abs/1902.01832 (2019) - [i29]Nikolaj Tatti:
Dynamic hierarchies in temporal directed networks. CoRR abs/1902.01873 (2019) - [i28]Nikolaj Tatti, Jilles Vreeken:
Finding Good Itemsets by Packing Data. CoRR abs/1902.02392 (2019) - [i27]Nikolaj Tatti:
Significance of Episodes Based on Minimal Windows. CoRR abs/1902.02755 (2019) - [i26]Nikolaj Tatti, Jilles Vreeken:
The Long and the Short of It: Summarising Event Sequences with Serial Episodes. CoRR abs/1902.02834 (2019) - [i25]Nikolaj Tatti, Jilles Vreeken:
Discovering Descriptive Tile Trees by Mining Optimal Geometric Subtiles. CoRR abs/1902.02861 (2019) - [i24]Nikolaj Tatti:
Are your Items in Order? CoRR abs/1902.02921 (2019) - [i23]Nikolaj Tatti, Michael Mampaey:
Using Background Knowledge to Rank Itemsets. CoRR abs/1902.03102 (2019) - [i22]Nikolaj Tatti:
Fast Sequence Segmentation using Log-Linear Models. CoRR abs/1902.03285 (2019) - [i21]Nikolaj Tatti:
Probably the Best Itemsets. CoRR abs/1902.03297 (2019) - [i20]Nikolaj Tatti, Fabian Moerchen:
Finding Robust Itemsets Under Subsampling. CoRR abs/1902.06743 (2019) - [i19]Nikolaj Tatti, Jilles Vreeken:
Comparing Apples and Oranges: Measuring Differences between Data Mining Results. CoRR abs/1902.07165 (2019) - [i18]Nikolaj Tatti:
Hierarchies in directed networks. CoRR abs/1903.02999 (2019) - [i17]Nikolaj Tatti, Aristides Gionis:
Density-friendly Graph Decomposition. CoRR abs/1904.03467 (2019) - [i16]Nikolaj Tatti:
Discovering Bands from Graphs. CoRR abs/1904.04403 (2019) - [i15]Nikolaj Tatti:
Discovering Episodes with Compact Minimal Windows. CoRR abs/1904.07974 (2019) - [i14]Nikolaj Tatti, Boris Cule:
Mining Closed Episodes with Simultaneous Events. CoRR abs/1904.08741 (2019) - [i13]Nikolaj Tatti, Boris Cule:
Mining Closed Strict Episodes. CoRR abs/1904.09231 (2019) - [i12]Nikolaj Tatti:
Maximum Entropy Based Significance of Itemsets. CoRR abs/1904.10632 (2019) - [i11]Michael Mampaey, Jilles Vreeken, Nikolaj Tatti:
Summarizing Data Succinctly with the Most Informative Itemsets. CoRR abs/1904.11134 (2019) - 2018
- [j26]Hao Wu, Maoyuan Sun, Peng Mi, Nikolaj Tatti, Chris North, Naren Ramakrishnan:
Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy Models. ACM Trans. Knowl. Discov. Data 12(1): 7:1-7:34 (2018) - [j25]Hao Wu, Yue Ning, Prithwish Chakraborty, Jilles Vreeken, Nikolaj Tatti, Naren Ramakrishnan:
Generating Realistic Synthetic Population Datasets. ACM Trans. Knowl. Discov. Data 12(4): 45:1-45:22 (2018) - [c36]Polina Rozenshtein, Francesco Bonchi, Aristides Gionis, Mauro Sozio, Nikolaj Tatti:
Finding Events in Temporal Networks: Segmentation Meets Densest-Subgraph Discovery. ICDM 2018: 397-406 - [c35]Nikolaj Tatti:
Dynamic Hierarchies in Temporal Directed Networks. ECML/PKDD (2) 2018: 55-70 - [c34]Esther Galbrun, Peggy Cellier, Nikolaj Tatti, Alexandre Termier, Bruno Crémilleux:
Mining Periodic Patterns with a MDL Criterion. ECML/PKDD (2) 2018: 535-551 - [c33]Nikolaj Tatti:
Efficient Estimation of AUC in a Sliding Window. ECML/PKDD (1) 2018: 671-686 - [c32]Han Xiao, Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
Reconstructing a cascade from temporal observations. SDM 2018: 666-674 - [i10]Han Xiao, Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
Reconstructing a cascade from temporal observations. CoRR abs/1801.08586 (2018) - [i9]Nikolaj Tatti:
Strongly polynomial efficient approximation scheme for segmentation. CoRR abs/1805.11170 (2018) - [i8]Esther Galbrun, Peggy Cellier, Nikolaj Tatti, Alexandre Termier, Bruno Crémilleux:
Mining Periodic Patterns with a MDL Criterion. CoRR abs/1807.01706 (2018) - [i7]Polina Rozenshtein, Francesco Bonchi, Aristides Gionis, Mauro Sozio, Nikolaj Tatti:
Finding events in temporal networks: Segmentation meets densest-subgraph discovery. CoRR abs/1808.09317 (2018) - 2017
- [j24]Nikolaj Tatti:
Tiers for peers: a practical algorithm for discovering hierarchy in weighted networks. Data Min. Knowl. Discov. 31(3): 702-738 (2017) - [j23]Orestis Kostakis, Nikolaj Tatti, Aristides Gionis:
Discovering recurring activity in temporal networks. Data Min. Knowl. Discov. 31(6): 1840-1871 (2017) - [j22]Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
Finding Dynamic Dense Subgraphs. ACM Trans. Knowl. Discov. Data 11(3): 27:1-27:30 (2017) - [c31]Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
Inferring the Strength of Social Ties: A Community-Driven Approach. KDD 2017: 1017-1025 - [c30]Kiran Garimella, Aristides Gionis, Nikos Parotsidis, Nikolaj Tatti:
Balancing information exposure in social networks. NIPS 2017: 4663-4671 - [c29]Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
The Network-Untangling Problem: From Interactions to Activity Timelines. ECML/PKDD (1) 2017: 701-716 - [c28]Aristides Gionis, Polina Rozenshtein, Nikolaj Tatti, Evimaria Terzi:
Community-aware network sparsification. SDM 2017: 426-434 - [c27]Nikolaj Tatti:
Discovering bursts revisited: guaranteed optimization of the model parameters. SDM 2017: 831-839 - [i6]Aristides Gionis, Polina Rozenshtein, Nikolaj Tatti, Evimaria Terzi:
Community-aware network sparsification. CoRR abs/1701.07221 (2017) - [i5]Kiran Garimella, Aristides Gionis, Nikos Parotsidis, Nikolaj Tatti:
Balancing Information Exposure in Social Networks. CoRR abs/1709.01491 (2017) - 2016
- [j21]François Petitjean, Tao Li, Nikolaj Tatti, Geoffrey I. Webb:
Skopus: Mining top-k sequential patterns under leverage. Data Min. Knowl. Discov. 30(5): 1086-1111 (2016) - [j20]Esther Galbrun, Aristides Gionis, Nikolaj Tatti:
Top-k overlapping densest subgraphs. Data Min. Knowl. Discov. 30(5): 1134-1165 (2016) - [c26]Albert Arockiasamy, Aristides Gionis, Nikolaj Tatti:
A Combinatorial Approach to Role Discovery. ICDM 2016: 787-792 - [e1]Bettina Berendt, Björn Bringmann, Élisa Fromont, Gemma C. Garriga, Pauli Miettinen, Nikolaj Tatti, Volker Tresp:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part III. Lecture Notes in Computer Science 9853, Springer 2016, ISBN 978-3-319-46130-4 [contents] - [i4]Hao Wu, Yue Ning, Prithwish Chakraborty, Jilles Vreeken, Nikolaj Tatti, Naren Ramakrishnan:
Generating Realistic Synthetic Population Datasets. CoRR abs/1602.06844 (2016) - [i3]Indre Zliobaite, Nikolaj Tatti:
A note on adjusting $R^2$ for using with cross-validation. CoRR abs/1605.01703 (2016) - [i2]Hao Wu, Maoyuan Sun, Jilles Vreeken, Nikolaj Tatti, Chris North, Naren Ramakrishnan:
Interactive and Iterative Discovery of Entity Network Subgraphs. CoRR abs/1608.03889 (2016) - 2015
- [j19]Eric Malmi, Nikolaj Tatti, Aristides Gionis:
Beyond rankings: comparing directed acyclic graphs. Data Min. Knowl. Discov. 29(5): 1233-1257 (2015) - [j18]Nikolaj Tatti:
Ranking episodes using a partition model. Data Min. Knowl. Discov. 29(5): 1312-1342 (2015) - [c25]Nikolaj Tatti:
Hierarchies in Directed Networks. ICDM 2015: 991-996 - [c24]Rohit Kumar, Toon Calders, Aristides Gionis, Nikolaj Tatti:
Maintaining Sliding-Window Neighborhood Profiles in Interaction Networks. ECML/PKDD (2) 2015: 719-735 - [c23]Nikolaj Tatti, Aristides Gionis:
Density-friendly Graph Decomposition. WWW 2015: 1089-1099 - [i1]Hao Wu, Maoyuan Sun, Peng Mi, Nikolaj Tatti, Chris North, Naren Ramakrishnan:
Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy Models. CoRR abs/1512.08799 (2015) - 2014
- [j17]Nikolaj Tatti:
Discovering episodes with compact minimal windows. Data Min. Knowl. Discov. 28(4): 1046-1077 (2014) - [j16]Hao Wu, Jilles Vreeken, Nikolaj Tatti, Naren Ramakrishnan:
Uncovering the plot: detecting surprising coalitions of entities in multi-relational schemas. Data Min. Knowl. Discov. 28(5-6): 1398-1428 (2014) - [j15]Nikolaj Tatti:
Discovering bands from graphs. Data Min. Knowl. Discov. 28(5-6): 1429-1454 (2014) - [j14]Esther Galbrun, Aristides Gionis, Nikolaj Tatti:
Overlapping community detection in labeled graphs. Data Min. Knowl. Discov. 28(5-6): 1586-1610 (2014) - [j13]Boris Cule, Nikolaj Tatti, Bart Goethals:
MARBLES: Mining association rules buried in long event sequences. Stat. Anal. Data Min. 7(2): 93-110 (2014) - [j12]Aparna S. Varde, Nikolaj Tatti:
A Panorama of Imminent Doctoral Research in Data Mining. SIGMOD Rec. 43(3): 71-74 (2014) - [j11]Nikolaj Tatti, Fabian Moerchen, Toon Calders:
Finding Robust Itemsets under Subsampling. ACM Trans. Database Syst. 39(3): 20:1-20:27 (2014) - [c22]Polina Rozenshtein, Aris Anagnostopoulos, Aristides Gionis, Nikolaj Tatti:
Event detection in activity networks. KDD 2014: 1176-1185 - [c21]Nikolaj Tatti:
Faster Way to Agony - Discovering Hierarchies in Directed Graphs. ECML/PKDD (3) 2014: 163-178 - [c20]Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
Discovering Dynamic Communities in Interaction Networks. ECML/PKDD (2) 2014: 678-693 - [p1]Jilles Vreeken, Nikolaj Tatti:
Interesting Patterns. Frequent Pattern Mining 2014: 105-134 - 2013
- [j10]Nikolaj Tatti:
Fast sequence segmentation using log-linear models. Data Min. Knowl. Discov. 27(3): 421-441 (2013) - [c19]Nikolaj Tatti:
Itemsets for Real-Valued Datasets. ICDM 2013: 717-726 - [c18]Nikolaj Tatti, Aristides Gionis:
Discovering Nested Communities. ECML/PKDD (2) 2013: 32-47 - [c17]Leman Akoglu, Duen Horng Chau, Christos Faloutsos, Nikolaj Tatti, Hanghang Tong, Jilles Vreeken:
Mining Connection Pathways for Marked Nodes in Large Graphs. SDM 2013: 37-45 - 2012
- [j9]Nikolaj Tatti, Boris Cule:
Mining closed strict episodes. Data Min. Knowl. Discov. 25(1): 34-66 (2012) - [j8]Nikolaj Tatti, Jilles Vreeken:
Comparing apples and oranges: measuring differences between exploratory data mining results. Data Min. Knowl. Discov. 25(2): 173-207 (2012) - [j7]Michael Mampaey, Jilles Vreeken, Nikolaj Tatti:
Summarizing data succinctly with the most informative itemsets. ACM Trans. Knowl. Discov. Data 6(4): 16:1-16:42 (2012) - [c16]Nikolaj Tatti, Jilles Vreeken:
The long and the short of it: summarising event sequences with serial episodes. KDD 2012: 462-470 - [c15]Nikolaj Tatti, Jilles Vreeken:
Discovering Descriptive Tile Trees - By Mining Optimal Geometric Subtiles. ECML/PKDD (1) 2012: 9-24 - [c14]Boris Cule, Nikolaj Tatti, Bart Goethals:
MARBLES: Mining Association Rules Buried in Long Event Sequences. SDM 2012: 248-259 - 2011
- [c13]Nikolaj Tatti, Fabian Moerchen:
Finding Robust Itemsets under Subsampling. ICDM 2011: 705-714 - [c12]Michael Mampaey, Nikolaj Tatti, Jilles Vreeken:
Tell me what i need to know: succinctly summarizing data with itemsets. KDD 2011: 573-581 - [c11]Nikolaj Tatti, Boris Cule:
Mining closed episodes with simultaneous events. KDD 2011: 1172-1180 - [c10]Nikolaj Tatti, Jilles Vreeken:
Comparing Apples and Oranges - Measuring Differences between Data Mining Results. ECML/PKDD (3) 2011: 398-413 - [c9]Nikolaj Tatti:
Are your Items in Order. SDM 2011: 414-425 - 2010
- [j6]Nikolaj Tatti, Michael Mampaey:
Using background knowledge to rank itemsets. Data Min. Knowl. Discov. 21(2): 293-309 (2010) - [j5]Jilles Vreeken, Nikolaj Tatti, Bart Goethals:
Useful patterns (UP'10) ACM SIGKDD workshop report. SIGKDD Explor. 12(2): 56-58 (2010) - [c8]Nikolaj Tatti, Boris Cule:
Mining Closed Strict Episodes. ICDM 2010: 501-510 - [c7]Nikolaj Tatti:
Probably the best itemsets. KDD 2010: 293-302
2000 – 2009
- 2009
- [c6]Nikolaj Tatti:
Significance of Episodes Based on Minimal Windows. ICDM 2009: 513-522 - [c5]Sami Hanhijärvi, Markus Ojala, Niko Vuokko, Kai Puolamäki, Nikolaj Tatti, Heikki Mannila:
Tell me something I don't know: randomization strategies for iterative data mining. KDD 2009: 379-388 - 2008
- [b1]Nikolaj Tatti:
Advances in Mining Binary Data: Itemsets as Summaries. Aalto University, Espoo, Finland, 2008 - [j4]Nikolaj Tatti:
Maximum entropy based significance of itemsets. Knowl. Inf. Syst. 17(1): 57-77 (2008) - [c4]Nikolaj Tatti, Jilles Vreeken:
Finding Good Itemsets by Packing Data. ICDM 2008: 588-597 - [c3]Nikolaj Tatti, Hannes Heikinheimo:
Decomposable Families of Itemsets. ECML/PKDD (2) 2008: 472-487 - 2007
- [j3]Nikolaj Tatti:
Distances between Data Sets Based on Summary Statistics. J. Mach. Learn. Res. 8: 131-154 (2007) - [c2]Nikolaj Tatti:
Maximum Entropy Based Significance of Itemsets. ICDM 2007: 312-321 - 2006
- [j2]Nikolaj Tatti:
Safe projections of binary data sets. Acta Informatica 42(8-9): 617-638 (2006) - [j1]Nikolaj Tatti:
Computational complexity of queries based on itemsets. Inf. Process. Lett. 98(5): 183-187 (2006) - [c1]Nikolaj Tatti, Taneli Mielikäinen, Aristides Gionis, Heikki Mannila:
What is the Dimension of Your Binary Data? ICDM 2006: 603-612
Coauthor Index
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