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2020 – today
- 2023
[c44]Ruiying Yang, María Santamaría, Francesco Cricri, Honglei Zhang
, Jani Lainema, Ramin Ghaznavi Youvalari, Miska M. Hannuksela, Tapio Elomaa:
Overfitting NN loop-filters in video coding. VCIP 2023: 1-5- 2021
- [i2]Yi Zhou, Heikki Huttunen, Tapio Elomaa:
using multiple losses for accurate facial age estimation. CoRR abs/2106.09393 (2021)
2010 – 2019
- 2018
- [c43]Kati Stormi, Teemu Laine, Tapio Elomaa:
Feasibility of B2C Customer Relationship Analytics in the B2B Industrial Context. ECIS 2018: 61 - [c42]Ilari Kampman, Tapio Elomaa:
Hierarchical Clustering of High-Dimensional Data Without Global Dimensionality Reduction. ISMIS 2018: 236-246 - 2016
- [j17]Tomi Äijö, Pekka Jääskeläinen, Tapio Elomaa, Heikki Kultala, Jarmo Takala:
Integer Linear Programming-Based Scheduling for Transport Triggered Architectures. ACM Trans. Archit. Code Optim. 12(4): 59:1-59:22 (2016) - 2015
- [j16]Teemu J. Heinimäki, Tapio Elomaa:
Quality Measures for Improving Technology Trees. Int. J. Comput. Games Technol. 2015: 975371:1-975371:10 (2015) - [c41]Teemu J. Heinimäki, Tapio Elomaa:
Augmenting Technology Trees: Automation and Tool Support. VS-GAMES 2015: 1-8 - 2012
- [j15]Timo Aho, Bernard Zenko, Saso Dzeroski, Tapio Elomaa:
Multi-target regression with rule ensembles. J. Mach. Learn. Res. 13: 2367-2407 (2012) - 2011
- [j14]Tapio Elomaa, Petr Berka, Jan Rauch:
Special issue on data analysis methodologies for intelligent systems: guest editor's introduction. J. Intell. Inf. Syst. 37(3): 291-292 (2011) - [e5]Tapio Elomaa, Jaakko Hollmén, Heikki Mannila:
Discovery Science - 14th International Conference, DS 2011, Espoo, Finland, October 5-7, 2011. Proceedings. Lecture Notes in Computer Science 6926, Springer 2011, ISBN 978-3-642-24476-6 [contents] - [i1]Tapio Elomaa, Matti Kääriäinen:
An Analysis of Reduced Error Pruning. CoRR abs/1106.0668 (2011) - 2010
- [c40]Tapio Elomaa, Jussi Kujala:
Covering Analysis of the Greedy Algorithm for Partial Cover. Algorithms and Applications 2010: 102-113 - [p1]Matti Saarela, Tapio Elomaa, Keijo Ruohonen:
An Analysis of Relevance Vector Machine Regression. Advances in Machine Learning I 2010: 227-246 - [e4]Tapio Elomaa, Heikki Mannila, Pekka Orponen:
Algorithms and Applications, Essays Dedicated to Esko Ukkonen on the Occasion of His 60th Birthday. Lecture Notes in Computer Science 6060, Springer 2010, ISBN 978-3-642-12475-4 [contents]
2000 – 2009
- 2009
- [c39]Jussi Kujala, Timo Aho, Tapio Elomaa:
A Walk from 2-Norm SVM to 1-Norm SVM. ICDM 2009: 836-841 - [e3]Jan Rauch, Zbigniew W. Ras, Petr Berka, Tapio Elomaa:
Foundations of Intelligent Systems, 18th International Symposium, ISMIS 2009, Prague, Czech Republic, September 14-17, 2009. Proceedings. Lecture Notes in Computer Science 5722, Springer 2009, ISBN 978-3-642-04124-2 [contents] - 2008
- [j13]Jussi Kujala, Tapio Elomaa:
The cost of offline binary search tree algorithms and the complexity of the request sequence. Theor. Comput. Sci. 393(1-3): 231-239 (2008) - [c38]Timo Aho, Tapio Elomaa, Jussi Kujala:
Unsupervised Classifier Selection Based on Two-Sample Test. Discovery Science 2008: 28-39 - [c37]Tapio Elomaa, Petri Lehtinen, Matti Saarela:
Obtaining Low-Arity Discretizations from Online Data Streams. ISMIS 2008: 90-99 - [c36]Tapio Elomaa, Petri Lehtinen:
Maintaining Optimal Multi-way Splits for Numerical Attributes in Data Streams. PAKDD 2008: 544-553 - [c35]Jussi Kujala, Tapio Elomaa:
Ranking the Uniformity of Interval Pairs. ECML/PKDD (1) 2008: 640-655 - [c34]Timo Aho, Tapio Elomaa, Jussi Kujala:
Reducing Splaying by Taking Advantage of Working Sets. WEA 2008: 1-13 - 2007
- [c33]Jussi Kujala, Tapio Elomaa:
Following the Perturbed Leader to Gamble at Multi-armed Bandits. ALT 2007: 166-180 - [c32]Jussi Kujala, Tapio Elomaa:
Improved Algorithms for Univariate Discretization of Continuous Features. PKDD 2007: 188-199 - 2006
- [c31]Heidi Koivistoinen, Minna Ruuska, Tapio Elomaa:
A Voronoi Diagram Approach to Autonomous Clustering. Discovery Science 2006: 149-160 - [c30]Jussi Kujala, Tapio Elomaa:
Poketree: A Dynamically Competitive Data Structure with Good Worst-Case Performance. ISAAC 2006: 277-288 - [c29]Tapio Elomaa, Jussi Kujala, Juho Rousu:
Practical Approximation of Optimal Multivariate Discretization. ISMIS 2006: 612-621 - 2005
- [j12]Tapio Elomaa, Tuomo Malinen:
On look-ahead and pathology in decision tree learning. J. Exp. Theor. Artif. Intell. 17(1-2): 19-33 (2005) - [c28]Jussi Kujala, Tapio Elomaa:
On Following the Perturbed Leader in the Bandit Setting. ALT 2005: 371-385 - [c27]Tapio Elomaa, Jussi Kujala, Juho Rousu:
Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes. ECML 2005: 547-555 - [c26]Tapio Elomaa, Heidi Koivistoinen:
On Autonomous k-Means Clustering. ISMIS 2005: 228-236 - 2004
- [j11]Tapio Elomaa, Matti Kääriäinen:
The Difficulty of Reduced Error Pruning of Leveled Branching Programs. Ann. Math. Artif. Intell. 41(1): 111-124 (2004) - [j10]Tapio Elomaa, Juho Rousu:
Efficient Multisplitting Revisited: Optima-Preserving Elimination of Partition Candidates. Data Min. Knowl. Discov. 8(2): 97-126 (2004) - [j9]Matti Kääriäinen, Tuomo Malinen, Tapio Elomaa:
Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees. J. Mach. Learn. Res. 5: 1107-1126 (2004) - 2003
- [j8]Richard Nock, Tapio Elomaa, Matti Kääriäinen:
Reduced Error Pruning of branching programs cannot be approximated to within a logarithmic factor. Inf. Process. Lett. 87(2): 73-78 (2003) - [j7]Tapio Elomaa, Juho Rousu:
Necessary and Sufficient Pre-processing in Numerical Range Discretization. Knowl. Inf. Syst. 5(2): 162-182 (2003) - [j6]Ilkka Autio, Tapio Elomaa:
Flexible view recognition for indoor navigation based on Gabor filters and support vector machines. Pattern Recognit. 36(12): 2769-2779 (2003) - [c25]Matti Kääriäinen, Tapio Elomaa:
Rademacher Penalization over Decision Tree Prunings. ECML 2003: 193-204 - [c24]Tapio Elomaa, Tuomo Malinen:
On Lookahead Heuristics in Decision Tree Learning. ISMIS 2003: 445-453 - [c23]Tapio Elomaa, Juho Rousu:
On Decision Boundaries of Naïve Bayes in Continuous Domains. PKDD 2003: 144-155 - 2002
- [j5]Tapio Elomaa, Juho Rousu:
Linear-Time Preprocessing in Optimal Numerical Range Partitioning. J. Intell. Inf. Syst. 18(1): 55-70 (2002) - [c22]Tapio Elomaa, Matti Kääriäinen:
Progressive Rademacher Sampling. AAAI/IAAI 2002: 140-145 - [c21]Tapio Elomaa, Jussi T. Lindgren:
Experiments with Projection Learning. Discovery Science 2002: 127-140 - [c20]Tapio Elomaa, Juho Rousu:
Fast Minimum Training Error Discretization. ICML 2002: 131-138 - [c19]Tapio Elomaa, Matti Kääriäinen:
The Difficulty of Reduced Error Pruning of Leveled Branching Programs. AI&M 2002 - [c18]Tapio Elomaa:
Partition-Refining Algorithms for Learning Finite State Automata. ISMIS 2002: 232-243 - [e2]Tapio Elomaa, Heikki Mannila, Hannu Toivonen:
Machine Learning: ECML 2002, 13th European Conference on Machine Learning, Helsinki, Finland, August 19-23, 2002, Proceedings. Lecture Notes in Computer Science 2430, Springer 2002, ISBN 3-540-44036-4 [contents] - [e1]Tapio Elomaa, Heikki Mannila, Hannu Toivonen:
Principles of Data Mining and Knowledge Discovery, 6th European Conference, PKDD 2002, Helsinki, Finland, August 19-23, 2002, Proceedings. Lecture Notes in Computer Science 2431, Springer 2002, ISBN 3-540-44037-2 [contents] - 2001
- [j4]Tapio Elomaa, Juho Rousu:
On the Computational Complexity of Optimal Multisplitting. Fundam. Informaticae 47(1-2): 35-52 (2001) - [j3]Tapio Elomaa, Matti Kääriäinen:
An Analysis of Reduced Error Pruning. J. Artif. Intell. Res. 15: 163-187 (2001) - [c17]Tapio Elomaa, Matti Kääriäinen:
On the Practice of Branching Program Boosting. ECML 2001: 133-144 - [c16]Tapio Elomaa, Juho Rousu:
Preprocessing Opportunities in Optimal Numerical Range Partitioning. ICDM 2001: 115-122 - [c15]Ilkka Autio, Tapio Elomaa, Teemu Kurppa:
Robot Landmark Learning with SVMs. SCAI 2001: 157-158 - 2000
- [c14]Tapio Elomaa, Juho Rousu:
Generalizing Boundary Points. AAAI/IAAI 2000: 570-576 - [c13]Tapio Elomaa, Juho Rousu:
On the Complexity of Optimal Multisplitting. ISMIS 2000: 552-561
1990 – 1999
- 1999
- [j2]Tapio Elomaa, Juho Rousu:
General and Efficient Multisplitting of Numerical Attributes. Mach. Learn. 36(3): 201-244 (1999) - [c12]Tapio Elomaa:
The Biases of Decision Tree Pruning Strategies. IDA 1999: 63-74 - [c11]Juho Rousu, Tapio Elomaa, Robert J. Aarts:
Predicting the Speed of Beer Fermentation in Laboratory and Industrial Scale. IWANN (2) 1999: 893-901 - [c10]Tapio Elomaa, Juho Rousu:
Speeding Up the Search for Optimal Partitions. PKDD 1999: 89-97 - 1998
- [j1]Tapio Elomaa:
A Review of How the Mind Works. AI Mag. 19(3): 135 (1998) - [c9]Tapio Elomaa, Juho Rousu:
Postponing the Evaluation of Attributes with a High Number of Boundary Points. PKDD 1998: 221-229 - 1997
- [c8]Tapio Elomaa, Juho Rousu:
Well-Behaved Evaluation Functions for Numerical Attributes. ISMIS 1997: 147-156 - [c7]Tapio Elomaa, Juho Rousu:
Efficient Multisplitting on Numerical Data. PKDD 1997: 178-188 - [c6]Tapio Elomaa, Juho Rousu:
On the Well-Behavedness of Important Attribute Evaluation Functions. SCAI 1997: 95-106 - 1995
- [c5]Tapio Elomaa, Niklas Holsti, Ilkka Hyvärinen:
TELA: A Platform for Experimenting with Attribute-based Learning Programs. SCAI 1995: 392-395 - 1994
- [c4]Tapio Elomaa, Esko Ukkonen:
A Geometric Approach to Feature Selection. ECML 1994: 351-354 - [c3]Tapio Elomaa:
In Defense of C4.5: Notes in Learning One-Level Decision Trees. ICML 1994: 62-69 - 1991
- [c2]Tapio Elomaa:
Extending the learnability of decision trees. ICTAI 1991: 504-505 - 1990
- [c1]Tapio Elomaa, Jyrki Kivinen:
On inducing topologically minimal decision trees. TAI 1990: 746-752
Coauthor Index
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