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2020 – today
- 2024
[i12]Risto Luukkonen, Jonathan Burdge, Elaine Zosa, Aarne Talman, Ville Komulainen, Väinö Hatanpää, Peter Sarlin, Sampo Pyysalo:
Poro 34B and the Blessing of Multilinguality. CoRR abs/2404.01856 (2024)- 2022
- [j22]Paola Cerchiello, Giancarlo Nicola, Samuel Rönnqvist, Peter Sarlin:
Assessing Banks' Distress Using News and Regular Financial Data. Frontiers Artif. Intell. 5: 871863 (2022) - [c34]Peter Sarlin, József Mezei:
Introduction to the Minitrack on Machine Learning and Predictive Analytics in Accounting, Finance, and Management. HICSS 2022: 1 - 2021
- [c33]Peter Sarlin, József Mezei:
Introduction to the Minitrack on Machine Learning and Predictive Analytics in Accounting, Finance, and Management. HICSS 2021: 1-2 - 2020
- [c32]József Mezei, Peter Sarlin:
Introduction to the Minitrack on Machine Learning and Predictive Analytics in Accounting, Finance and Management. HICSS 2020: 1-2
2010 – 2019
- 2019
- [c31]Peter Sarlin, József Mezei:
Introduction to the Minitrack on Machine Learning and Network Analytics in Finance. HICSS 2019: 1 - 2018
- [c30]Peter Sarlin, Paolo Giudici, Alessandro Spelta, Kaj-Mikael Björk:
Riskrank to Predict Systemic Banking Crises With Common Exposures. HICSS 2018: 1-9 - [c29]Peter Sarlin, József Mezei:
Introduction to the Minitrack on Machine Learning and Network Analytics in Finance. HICSS 2018: 1 - 2017
- [j21]Peter Sarlin
, Kaj-Mikael Björk:
Machine learning in finance - Guest editorial. Neurocomputing 264: 1 (2017) - [j20]Samuel Rönnqvist, Peter Sarlin:
Bank distress in the news: Describing events through deep learning. Neurocomputing 264: 57-70 (2017) - [c28]József Mezei, Peter Sarlin:
Possibilistic Clustering for Crisis Prediction: Systemic Risk States and Membership Degrees. HICSS 2017: 1-10 - [c27]Peter Sarlin, József Mezei:
Introduction to Machine Learning and Network Analytics in Finance Minitrack. HICSS 2017: 1 - [i11]Paola Cerchiello, Giancarlo Nicola, Samuel Rönnqvist, Peter Sarlin:
Deep learning bank distress from news and numerical financial data. CoRR abs/1706.09627 (2017) - 2016
- [j19]József Mezei, Peter Sarlin:
Aggregating expert knowledge for the measurement of systemic risk. Decis. Support Syst. 88: 38-50 (2016) - [j18]Peter Sarlin:
Computational Tools for Systemic Risk Identification and Assessment. Intell. Syst. Account. Finance Manag. 23(1-2): 3-5 (2016) - [j17]Peter Sarlin:
Visual Macroprudential Surveillance of Banks. Intell. Syst. Account. Finance Manag. 23(4): 257-264 (2016) - [c26]József Mezei, Peter Sarlin:
On interval-valued possibilistic clustering with a generalized objective function. FUZZ-IEEE 2016: 824-830 - [c25]Peter Sarlin, Tuomas A. Peltonen:
Introduction to Systemic Risk Analytics Minitrack. HICSS 2016: 1758 - [c24]Patrick Kouontchou, Amaury Lendasse, Yoan Miché, Alejandro Modesto, Peter Sarlin, Bertrand Maillet:
A R-SOM Analysis of the Link between Financial Market Conditions and a Systemic Risk Index Based on ICA-Factors of Systemic Risk Measures. HICSS 2016: 1759-1770 - [c23]József Mezei, Peter Sarlin:
On a Generalized Objective Function for Possibilistic Fuzzy Clustering. IPMU (1) 2016: 711-722 - [c22]Thomas Forss, Peter Sarlin:
From news to company networks: Co-occurrence, sentiment, and information centrality. SSCI 2016: 1-8 - [i10]Samuel Rönnqvist, Peter Sarlin:
Bank distress in the news: Describing events through deep learning. CoRR abs/1603.05670 (2016) - 2015
- [j16]Stephanie R. Clark, Peter Sarlin, Ashish Sharma, Scott A. Sisson:
Increasing dependence on foreign water resources? An assessment of trends in global virtual water flows using a self-organizing time map. Ecol. Informatics 26(2): 192-202 (2015) - [j15]Peter Sarlin:
Data and dimension reduction for visual financial performance analysis. Inf. Vis. 14(2): 148-167 (2015) - [j14]Peter Sarlin:
Automated and weighted self-organizing time maps. Knowl. Inf. Syst. 44(2): 493-505 (2015) - [c21]Samuel Rönnqvist, Peter Sarlin:
Detect & Describe: Deep Learning of Bank Stress in the News. SSCI 2015: 890-897 - [c20]Markus Holopainen, Peter Sarlin:
Crisis Modeler: A Tool for Exploring Crisis Predictions. SSCI 2015: 917-924 - [i9]Markus Holopainen, Peter Sarlin:
Toward robust early-warning models: A horse race, ensembles and model uncertainty. CoRR abs/1501.04682 (2015) - [i8]Samuel Rönnqvist, Peter Sarlin:
Detect & Describe: Deep learning of bank stress in the news. CoRR abs/1507.07870 (2015) - 2014
- [b1]Peter Sarlin:
Mapping Financial Stability. Computational Risk Management, Springer 2014, ISBN 978-3-642-54955-7, pp. 1-233 - [j13]Peter Sarlin:
A weighted SOM for classifying data with instance-varying importance. Int. J. Mach. Learn. Cybern. 5(1): 101-110 (2014) - [j12]Peter Sarlin:
On biologically inspired predictions of the global financial crisis. Neural Comput. Appl. 24(3-4): 663-673 (2014) - [j11]Zhiyuan Yao, Peter Sarlin, Tomas Eklund, Barbro Back:
Combining visual customer segmentation and response modeling. Neural Comput. Appl. 25(1): 123-134 (2014) - [c19]Samuel Rönnqvist, Peter Sarlin:
From text to bank interrelation maps. CIFEr 2014: 48-54 - [c18]Henrik J. Nyman, Peter Sarlin:
From Bits to Atoms: 3D Printing in the Context of Supply Chain Strategies. HICSS 2014: 4190-4199 - [i7]Samuel Rönnqvist, Xiaolu Wang, Peter Sarlin:
Interactive Visual Exploration of Topic Models using Graphs. CoRR abs/1409.5623 (2014) - [i6]József Mezei, Peter Sarlin:
Aggregation operators for the measurement of systemic risk. CoRR abs/1412.5452 (2014) - 2013
- [j10]Peter Sarlin:
Exploiting the self-organizing financial stability map. Eng. Appl. Artif. Intell. 26(5-6): 1532-1539 (2013) - [j9]Peter Sarlin:
Self-organizing time map: An abstraction of temporal multivariate patterns. Neurocomputing 99: 496-508 (2013) - [j8]Peter Sarlin, Zhiyuan Yao:
Clustering of the Self-Organizing Time Map. Neurocomputing 121: 317-327 (2013) - [j7]Peter Sarlin, Tomas Eklund:
Financial performance analysis of European banks using a fuzzified Self-Organizing Map. Int. J. Knowl. Based Intell. Eng. Syst. 17(3): 223-234 (2013) - [j6]Peter Sarlin:
Decomposing the global financial crisis: A Self-Organizing Time Map. Pattern Recognit. Lett. 34(14): 1701-1709 (2013) - [c17]Peter Sarlin:
A Self-Organizing Time Map for time-to-event data. CIDM 2013: 230-237 - [c16]Annika H. Holmbom, Samuel Rönnqvist, Peter Sarlin, Tomas Eklund, Barbro Back:
Green vs. Non-Green Customer Behavior: A Self-Organizing Time Map over Greenness. ICDM Workshops 2013: 529-535 - [c15]Annika H. Holmbom, Peter Sarlin, Zhiyuan Yao, Tomas Eklund, Barbro Back:
Visual Data-Driven Profiling of Green Consumers. IV 2013: 291-298 - [c14]Peter Sarlin, Samuel Rönnqvist:
Cluster Coloring of the Self-Organizing Map: An Information Visualization Perspective. IV 2013: 532-538 - [i5]Samuel Rönnqvist, Peter Sarlin:
From Text to Bank Interrelation Maps. CoRR abs/1306.3856 (2013) - [i4]Peter Sarlin, Samuel Rönnqvist:
Cluster coloring of the Self-Organizing Map: An information visualization perspective. CoRR abs/1306.3860 (2013) - [i3]Henrik J. Nyman, Peter Sarlin:
From Bits to Atoms: 3D Printing in the Context of Supply Chain Strategies. CoRR abs/1306.4512 (2013) - [i2]Peter Sarlin:
Automated and Weighted Self-Organizing Time Maps. CoRR abs/1311.5763 (2013) - 2012
- [j5]Peter Sarlin, Zhiyuan Yao, Tomas Eklund:
A Framework for State Transitions on the Self-Organizing Map: some Temporal Financial Applications. Intell. Syst. Account. Finance Manag. 19(3): 189-203 (2012) - [j4]Peter Sarlin:
Visual tracking of the millennium development goals with a fuzzified self-organizing neural network. Int. J. Mach. Learn. Cybern. 3(3): 233-245 (2012) - [c13]Zhiyuan Yao, Peter Sarlin, Tomas Eklund, Barbro Back:
Combining Visual Customer Segmentation and Response Modeling. ECIS 2012: 143 - [c12]Peter Sarlin:
On Biologically Inspired Predictions Of The Global Financial Crisis. ECMS 2012: 253-259 - [c11]Peter Sarlin, Zhiyuan Yao, Tomas Eklund:
Probabilistic Modeling of State Transitions on the Self-Organizing Map: Some Temporal Financial Applications. HICSS 2012: 1128-1137 - [c10]Peter Sarlin:
A Weighted SOM for Classifying Data with Instance-Varying Importance. ICDM Workshops 2012: 187-193 - [c9]Zhiyuan Yao, Peter Sarlin, Tomas Eklund, Barbro Back:
Temporal Customer Segmentation Using the Self-organizing Time Map. IV 2012: 234-240 - [c8]Peter Sarlin:
Exploiting the Self-Organizing Financial Stability Map. KES 2012: 248-257 - [c7]Peter Sarlin:
Decomposing the Global Financial Crisis: A Self-Organizing Time Map. KES 2012: 798-806 - [i1]Peter Sarlin:
Self-Organizing Time Map: An Abstraction of Temporal Multivariate Patterns. CoRR abs/1208.1819 (2012) - 2011
- [j3]Peter Sarlin, Dorina Marghescu:
Visual predictions of currency crises using self-organizing maps. Intell. Syst. Account. Finance Manag. 18(1): 15-38 (2011) - [j2]Peter Sarlin, Dorina Marghescu:
Neuro-Genetic Predictions of Currency crises. Intell. Syst. Account. Finance Manag. 18(4): 145-160 (2011) - [c6]Peter Sarlin:
Visual tracking of the Millennium Development Goals with a Self-organizing neural network. CIDM 2011: 357-364 - [c5]Peter Sarlin:
Sovereign debt monitor: A visual Self-organizing maps approach. CIFEr 2011: 67-64 - [c4]Peter Sarlin, Tomas Eklund:
Financial Performance Analysis of European Banks Using a Fuzzified Self-Organizing Map. KES (2) 2011: 186-195 - [c3]Peter Sarlin, Tomas Eklund:
Fuzzy Clustering of the Self-Organizing Map: Some Applications on Financial Time Series. WSOM 2011: 40-50 - 2010
- [j1]Dorina Marghescu, Peter Sarlin, Shuhua Liu:
Early-warning analysis for currency crises in emerging markets: A revisit with fuzzy clustering. Intell. Syst. Account. Finance Manag. 17(3-4): 143-165 (2010) - [c2]Peter Sarlin, Dorina Marghescu:
Visual Predictions of Currency Crises Using Self-Organizing Maps. ICDM Workshops 2010: 623-630 - [c1]Peter Sarlin:
Visual monitoring of financial stability with a self-organizing neural network. ISDA 2010: 248-253
Coauthor Index
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last updated on 2024-05-10 00:43 CEST by the dblp team
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