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Igor Vatolkin [Peer-Reviewed Conference Proceedings]
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+====== Publication List ======
 ===== Edited Books =====
-<html><b><font color=#006633>[1]</font></b> <i>C. Weihs, D. Jannach, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Music Data Analysis: Foundations and Applications. </font></b> CRC Press, <html><font color=#996600>07.11.2016</font></html>
+<html><b><font color=#006633>[b1]</font></b> <i>C. Weihs, D. Jannach, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Music Data Analysis: Foundations and Applications. </font></b> CRC Press, <html><font color=#996600>07.11.2016</font></html>
-===== Book Chapters =====
+===== Journal Articles =====
+<html><b><font color=#006633>[j8]</font></b> <i>I. Vatolkin and C. McKay</i>:<b><font color=#0000FF> Multi-Objective Investigation of Six Feature Source Types for Multi-Modal Music Classification</font></b>. Transactions of the International Society for Music Information Retrieval, 5(1):1-19, <html><font color=#996600>2022</font></html>
-<html><b><font color=#006633>[6]</font></b> <i>I. Vatolkin, C. Weihs</i>:<b><font color=#0000FF> Evaluation</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[j7]</font></b> <i>F. Ostermann, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Evaluating Creativity in Automatic Reactive Accompaniment of Jazz Improvisation</font></b>. Transactions of the International Society for Music Information Retrieval, 4(1):210-222, <html><font color=#996600>2021</font></html>
-<html><b><font color=#006633>[5]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Feature Processing</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[j6]</font></b> <i>B. Wilkes, I. Vatolkin, and H. Müller</i>:<b><font color=#0000FF> Statistical and Visual Analysis of Audio, Text, and Image Features for Multi-Modal Music Genre Recognition</font></b>. Entropy, 23(11), <html><font color=#996600>2021</font></html>
-<html><b><font color=#006633>[4]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Feature Selection</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[j5]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Robustness of Features and Classification Models on Degraded Data Sets in Music Classification</font></b>. Archives of Data Science, Series A, 5(1), <html><font color=#996600>2018</font></html>
-<html><b><font color=#006633>[3]</font></b> <i>G. Rötter, I. Vatolkin</i>:<b><font color=#0000FF> Emotions</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[j4]</font></b> <i>A. K. Hassen, H. Janßen, D. Assenmacher, M. Preuss, and I. Vatolkin</i>:<b><font color=#0000FF> Classifying Music Genres Using Image Classification Neural Networks</font></b>. Archives of Data Science, Series A, 5(1), <html><font color=#996600>2018</font></html>
-<html><b><font color=#006633>[2]</font></b> <i>D. Jannach, I. Vatolkin, and G. Bonnin</i>:<b><font color=#0000FF> Music Data: beyond the Signal Level</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[j3]</font></b> <i>D. Stoller, I. Vatolkin, and H. Müller</i>:<b><font color=#0000FF> Intuitive and Efficient Computer-Aided Music Rearrangement with Optimised Processing of Audio Transitions</font></b>. Journal of New Music Research, 47(5):416-437, <html><font color=#996600>2018</font></html>
-<html><b><font color=#006633>[1]</font></b> <i>N. Bauer, S. Krey, U. Ligges, C. Weihs, and I. Vatolkin</i>:<b><font color=#0000FF> Segmentation</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[j2]</font></b> <i>I. Vatolkin, M. Preuß, G. Rudolph, M. Eichhoff, and C. Weihs</i>:<b><font color=#0000FF> Multi-Objective Evolutionary Feature Selection for Instrument Recognition in Polyphonic Audio Mixtures</font></b>. Soft Computing – A Fusion of Foundations, Methodologies and Applications, 16(12):2027-2047, <html><font color=#996600>2012</font></html>
-===== Journal Articles =====
+<html><b><font color=#006633>[j1]</font></b> <i>H. Blume, B. Bischl, M. Botteck, C. Igel, R. Martin, G. Rötter, G. Rudolph, W. Theimer, I. Vatolkin, and C. Weihs</i>:<b><font color=#0000FF> Towards an Automated Dynamic Organization of Huge Music Archives on Mobile Devices</font></b>. IEEE Signal Processing Magazine, 28(4):24-39, July <html><font color=#996600>2011</font></html>
-<html><b><font color=#006633>[3]</font></b> <i>D. Stoller, I. Vatolkin, H. Müller</i>:<b><font color=#0000FF> Intuitive and Efficient Computer-Aided Music Rearrangement with Optimised Processing of Audio Transitions</font></b>. Accepted for Journal of New Music Research, <html><font color=#996600>2018</font></html>
-<html><b><font color=#006633>[2]</font></b> <i>I. Vatolkin, M. Preuß, G. Rudolph, M. Eichhoff, and C. Weihs</i>:<b><font color=#0000FF> Multi-Objective Evolutionary Feature Selection for Instrument Recognition in Polyphonic Audio Mixtures</font></b>. Soft Computing – A Fusion of Foundations, Methodologies and Applications, 16(12):2027-2047, <html><font color=#996600>2012</font></html>
+===== Book Chapters =====
-<html><b><font color=#006633>[1]</font></b> <i>H. Blume, B. Bischl, M. Botteck, C. Igel, R. Martin, G. Rötter, G. Rudolph, W. Theimer, I. Vatolkin, and C. Weihs</i>:<b><font color=#0000FF> Towards an Automated Dynamic Organization of Huge Music Archives on Mobile Devices</font></b>. IEEE Signal Processing Magazine, 28(4):24-39, July <html><font color=#996600>2011</font></html>
+<html><b><font color=#006633>[bc7]</font></b> <i>I. Vatolkin, A. Nagathil</i>:<b><font color=#0000FF> Evaluation of Audio Feature Groups for the Prediction of Arousal and Valence in Music</font></b>. In: N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, M. Vichi (Eds.) (Eds.): Applications in Statistical Computing: From Music Data Analysis to Industrial Quality Improvement, Springer, <html><font color=#996600>2019</font></html>
+<html><b><font color=#006633>[bc6]</font></b> <i>I. Vatolkin, C. Weihs</i>:<b><font color=#0000FF> Evaluation</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[bc5]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Feature Processing</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[bc4]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Feature Selection</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[bc3]</font></b> <i>G. Rötter, I. Vatolkin</i>:<b><font color=#0000FF> Emotions</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[bc2]</font></b> <i>D. Jannach, I. Vatolkin, and G. Bonnin</i>:<b><font color=#0000FF> Music Data: beyond the Signal Level</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
+<html><b><font color=#006633>[bc1]</font></b> <i>N. Bauer, S. Krey, U. Ligges, C. Weihs, and I. Vatolkin</i>:<b><font color=#0000FF> Segmentation</font></b>. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications, CRC Press, <html><font color=#996600>2016</font></html>
 ===== Peer-Reviewed Conference Proceedings =====
-<html><b><font color=#006633>[29]</font></b> <i> I. Vatolkin and D. Stoller</i>:<b><font color=#0000FF> Evolutionary Multi-Objective Training Set Selection of Data Instances and Augmentations for Vocal Detection</font></b>. Accepted for Proceedings of the 8th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), <font color=#996600>2019</font></html>
+<html><b><font color=#006633>[c43]</font></b> <i> L. Fricke, I. Vatolkin, and F. Ostermann</i>:<b><font color=#0000FF> Application of Neural Architecture Search to Instrument Recognition in Polyphonic Audio</font></b>. Accepted for Proceedings of the 12th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), <font color=#996600>2023</font></html>
+<html><b><font color=#006633>[c42]</font></b> <i> I. Vatolkin, M. Gotham, N. Nápoles López, and F. Ostermann</i>:<b><font color=#0000FF> Musical Genre Recognition based on Deep Descriptors of Harmony, Instrumentation, and Segments</font></b>. Accepted for Proceedings of the 12th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), <font color=#996600>2023</font></html>
+<html><b><font color=#006633>[c41]</font></b> <i> L. Fricke, J. Kuzmic, and I. Vatolkin</i>:<b><font color=#0000FF> Suppression of Background Noise in Speech Signals with Artificial Neural Networks, Exemplarily Applied to Keyboard Sounds</font></b>. Proceedings of the 14th International Conference on Neural Computation Theory and Applications (NCTA), pp. 367-374, <font color=#996600>2022</font></html>
+<html><b><font color=#006633>[c40]</font></b> <i> I. Vatolkin and C. McKay</i>:<b><font color=#0000FF> Stability of Symbolic Feature Group Importance in the Context of Multi-Modal Music Classification</font></b>. Proceedings of the The 23rd International Society for Music Information Retrieval Conference (ISMIR), pp.469-476, <font color=#996600>2022</font></html>
+<html><b><font color=#006633>[c39]</font></b> <i> F. Ostermann, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Artificial Music Producer: Filtering Music Compositions by Artificial Taste</font></b>. Proceedings of the 3rd Conference on AI Music Creativity (AIMC), <font color=#996600>2022</font></html>
+<html><b><font color=#006633>[c38]</font></b> <i> I. Vatolkin</i>:<b><font color=#0000FF> Identification of the Most Relevant Zygonic Statistics and Semantic Audio Features for Genre Recognition</font></b>. Proceedings of the International Computer Music Conference (ICMC), <font color=#996600>2022</font></html>
+<html><b><font color=#006633>[c37]</font></b> <i> I. Vatolkin</i>:<b><font color=#0000FF> Improving Interpretable Genre Recognition with Audio Feature Statistics Based on Zygonic Theory</font></b>. Proceedings of the 2nd Nordic Sound and Computing Conference (NordicSMC), <font color=#996600>2021</font></html>
+<html><b><font color=#006633>[c36]</font></b> <i> I. Vatolkin, P. Ginsel, and G. Rudolph</i>:<b><font color=#0000FF> Advancements in the Music Information Retrieval Framework AMUSE over the Last Decade</font></b>. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pp. 2383-2389, <font color=#996600>2021</font></html>
+<html><b><font color=#006633>[c35]</font></b> <i> I. Vatolkin, F. Ostermann, and M. Müller</i>:<b><font color=#0000FF> An Evolutionary Multi-Objective Feature Selection Approach for Detecting Music Segment Boundaries of Specific Types</font></b>. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 1061-1069, <font color=#996600>2021</font></html>
+<html><b><font color=#006633>[c34]</font></b> <i> I. Vatolkin, B. Adrian, and J. Kuzmic</i>:<b><font color=#0000FF> A Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features</font></b>. Proceedings of the 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 313-326, <font color=#996600>2021</font></html>
+<html><b><font color=#006633>[c33]</font></b> <i> I. Vatolkin, M. Koch, and M. Müller</i>:<b><font color=#0000FF> A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation</font></b>. Proceedings of the 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 327-343, <font color=#996600>2021</font></html>
+<html><b><font color=#006633>[c32]</font></b> <i> I. Vatolkin</i>:<b><font color=#0000FF> Evolutionary Approximation of Instrumental Texture in Polyphonic Audio Recordings</font></b>. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pp. 1-8, <font color=#996600>2020</font></html>
+<html><b><font color=#006633>[c31]</font></b> <i> P. Ginsel, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Analysis of Structural Complexity Features for Music Genre Recognition</font></b>. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pp. 1-8, <font color=#996600>2020</font></html>
+<html><b><font color=#006633>[c30]</font></b> <i> F. Heerde, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Comparing Fuzzy Rule Based Approaches for Music Genre Classification</font></b>. Proceedings of the 9th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 35-48, <font color=#996600>2020</font></html>
+<html><b><font color=#006633>[c29]</font></b> <i> I. Vatolkin and D. Stoller</i>:<b><font color=#0000FF> Evolutionary Multi-Objective Training Set Selection of Data Instances and Augmentations for Vocal Detection</font></b>. Proceedings of the 8th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 201-216, <font color=#996600>2019</font></html>
-<html><b><font color=#006633>[28]</font></b> <i> I. Vatolkin and G. Rudolph</i>:<b><font color=#0000FF> Comparison of Audio Features for Recognition of Western and Ethnic
+<html><b><font color=#006633>[c28]</font></b> <i> I. Vatolkin and G. Rudolph</i>:<b><font color=#0000FF> Comparison of Audio Features for Recognition of Western and Ethnic
-Instruments in Polyphonic Mixtures</font></b>. Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), pp. 554-560,<font color=#996600>2018</font></html>
+Instruments in Polyphonic Mixtures</font></b>. Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), pp. 554-560, <font color=#996600>2018</font></html>
-<html><b><font color=#006633>[27]</font></b> <i>F. Scholz, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Singing Voice Detection across Different Music Genres</font></b>. Proceedings of the 2017 AES Conference on Semantic Audio, <font color=#996600>2017</font></html>
+<html><b><font color=#006633>[c27]</font></b> <i>F. Scholz, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Singing Voice Detection across Different Music Genres</font></b>. Proceedings of the 2017 AES Conference on Semantic Audio, <font color=#996600>2017</font></html>
-<html><b><font color=#006633>[26]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Generalisation Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples</font></b>. Proceedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 304-320, <font color=#996600>2017</font></html>
+<html><b><font color=#006633>[c26]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Generalisation Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples</font></b>. Proceedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 304-320, <font color=#996600>2017</font></html>
-<html><b><font color=#006633>[25]</font></b> <i>F. Ostermann, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Evaluation Rules for Evolutionary Generation of Drum Patterns in Jazz Solos</font></b>. Proceedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 246-261, <font color=#996600>2017</font></html>
+<html><b><font color=#006633>[c25]</font></b> <i>F. Ostermann, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Evaluation Rules for Evolutionary Generation of Drum Patterns in Jazz Solos</font></b>. Proceedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 246-261, <font color=#996600>2017</font></html>
-<html><b><font color=#006633>[24]</font></b> <i>I. Vatolkin, G. Rudolph, and C. Weihs</i>:<b><font color=#0000FF> Evaluation of Album Effect for Feature Selection in Music Genre Recognition</font></b>. Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR), pp. 169-175, <font color=#996600>2015</font></html>
+<html><b><font color=#006633>[c24]</font></b> <i>I. Vatolkin, G. Rudolph, and C. Weihs</i>:<b><font color=#0000FF> Evaluation of Album Effect for Feature Selection in Music Genre Recognition</font></b>. Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR), pp. 169-175, <font color=#996600>2015</font></html>
-<html><b><font color=#006633>[23]</font></b> <i>I. Vatolkin, G. Rudolph, and C. Weihs</i>:<b><font color=#0000FF> Interpretability of Music Classification as a Criterion for Evolutionary Multi-Objective Feature Selection</font></b>. Proceedings of the 4th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), pp. 236-248, <font color=#996600>2015</font></html>
+<html><b><font color=#006633>[c23]</font></b> <i>I. Vatolkin, G. Rudolph, and C. Weihs</i>:<b><font color=#0000FF> Interpretability of Music Classification as a Criterion for Evolutionary Multi-Objective Feature Selection</font></b>. Proceedings of the 4th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), pp. 236-248, <font color=#996600>2015</font></html>
-<html><b><font color=#006633>[22]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Exploration of Two-Objective Scenarios on Supervised Evolutionary Feature Selection: a Survey and a Case Study (Application to Music Categorisation)</font></b>. Proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization (EMO), pp. 529-543, <font color=#996600>2015</font></html>
+<html><b><font color=#006633>[c22]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Exploration of Two-Objective Scenarios on Supervised Evolutionary Feature Selection: a Survey and a Case Study (Application to Music Categorisation)</font></b>. Proceedings of the 8th International Conference on Evolutionary Multi-Criterion Optimization (EMO), pp. 529-543, <font color=#996600>2015</font></html>
-<html><b><font color=#006633>[21]</font></b> <i>I. Vatolkin. G. Bonnin, and D. Jannach</i>:<b><font color=#0000FF> Comparing Audio Features and Playlist Statistics for Music
+<html><b><font color=#006633>[c21]</font></b> <i>I. Vatolkin. G. Bonnin, and D. Jannach</i>:<b><font color=#0000FF> Comparing Audio Features and Playlist Statistics for Music
 Classification</font></b>. Proceedings of the 2nd European Conference on Data Analysis (ECDA 2014), pp. 437-447, <font color=#996600>2016</font></html>
-<html><b><font color=#006633>[20]</font></b> <i>I. Vatolkin and G. Rudolph</i>:<b><font color=#0000FF> Interpretable Music Categorisation based on Fuzzy Rules and High-Level Audio Features Features</font></b>. Proceedings of the 1st European Conference on Data Analysis (ECDA 2013), pp. 423-432, <font color=#996600>2015</font></html>
+<html><b><font color=#006633>[c20]</font></b> <i>I. Vatolkin and G. Rudolph</i>:<b><font color=#0000FF> Interpretable Music Categorisation based on Fuzzy Rules and High-Level Audio Features Features</font></b>. Proceedings of the 1st European Conference on Data Analysis (ECDA 2013), pp. 423-432, <font color=#996600>2015</font></html>
-<html><b><font color=#006633>[19]</font></b> <i>D. Stoller, M. Mauch, I. Vatolkin, and C. Weihs</i>:<b><font color=#0000FF> Impact of Frame Size and Instrumentation on Chroma-based Automatic Chord Recognition</font></b>. Proceedings of the 1st European Conference on Data Analysis (ECDA 2013), pp. 411-421, <span style="color:red;"><b>best paper award</b></span>, <font color=#996600>2015</font></html>
+<html><b><font color=#006633>[c19]</font></b> <i>D. Stoller, M. Mauch, I. Vatolkin, and C. Weihs</i>:<b><font color=#0000FF> Impact of Frame Size and Instrumentation on Chroma-based Automatic Chord Recognition</font></b>. Proceedings of the 1st European Conference on Data Analysis (ECDA 2013), pp. 411-421, <span style="color:red;"><b>best paper award</b></span>, <font color=#996600>2015</font></html>
-<html><b><font color=#006633>[18]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Measuring the Performance of Evolutionary Multi-Objective Feature Selection for Prediction of Musical Genres and Styles</font></b>. Proceedings of the 2nd Workshop Audiosignal- und Sprachverarbeitung (WASP) at INFORMATIK 2013, pp. 3012-3025, <font color=#996600>2013</font></html>
+<html><b><font color=#006633>[c18]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Measuring the Performance of Evolutionary Multi-Objective Feature Selection for Prediction of Musical Genres and Styles</font></b>. Proceedings of the 2nd Workshop Audiosignal- und Sprachverarbeitung (WASP) at INFORMATIK 2013, pp. 3012-3025, <font color=#996600>2013</font></html>
-<html><b><font color=#006633>[17]</font></b> <i>I. Vatolkin, A. Nagathil, W. Theimer, and R. Martin</i>:<b><font color=#0000FF> Performance of Specific vs. Generic Feature Sets in Polyphonic Music Instrument Recognition</font></b>. Proceedings of the 7th International Conference on Evolutionary Multi-Criterion Optimization (EMO), pp. 587-599, <font color=#996600>2013</font></html>
+<html><b><font color=#006633>[c17]</font></b> <i>I. Vatolkin, A. Nagathil, W. Theimer, and R. Martin</i>:<b><font color=#0000FF> Performance of Specific vs. Generic Feature Sets in Polyphonic Music Instrument Recognition</font></b>. Proceedings of the 7th International Conference on Evolutionary Multi-Criterion Optimization (EMO), pp. 587-599, <font color=#996600>2013</font></html>
-<html><b><font color=#006633>[16]</font></b> <i>I. Vatolkin, G. Rötter, and C. Weihs</i>:<b><font color=#0000FF> Music Genre Prediction by Low-Level and High-Level Characteristics</font></b>.  Accepted for Proceedings of the 36th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2012</font></html>
+<html><b><font color=#006633>[c16]</font></b> <i>I. Vatolkin, G. Rötter, and C. Weihs</i>:<b><font color=#0000FF> Music Genre Prediction by Low-Level and High-Level Characteristics</font></b>.  Accepted for Proceedings of the 36th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2012</font></html>
-<html><b><font color=#006633>[15]</font></b> <i>I. Vatolkin, B. Bischl, G. Rudolph, and C. Weihs</i>:<b><font color=#0000FF> Statistical Comparison of Classifiers for Multi-Objective Feature Selection in Instrument Recognition</font></b>.  Accepted for Proceedings of the 36th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2012</font></html>
+<html><b><font color=#006633>[c15]</font></b> <i>I. Vatolkin, B. Bischl, G. Rudolph, and C. Weihs</i>:<b><font color=#0000FF> Statistical Comparison of Classifiers for Multi-Objective Feature Selection in Instrument Recognition</font></b>.  Accepted for Proceedings of the 36th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2012</font></html>
-<html><b><font color=#006633>[14]</font></b> <i>A. Jordan, D. Scheftelowitsch, J. Lahni, J. Hartwecker, M. Kuchem, M. Walter-Huber, N. Vortmeier, T. Delbruegger, Ü. Güler, I. Vatolkin, and M. Preuss</i>:<b><font color=#0000FF> BeatTheBeat: Music-Based Procedural Content Generation In a Mobile Game</font></b>. Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games (CIG), pp. 320-327, <font color=#996600>2012</font></html>
+<html><b><font color=#006633>[c14]</font></b> <i>A. Jordan, D. Scheftelowitsch, J. Lahni, J. Hartwecker, M. Kuchem, M. Walter-Huber, N. Vortmeier, T. Delbruegger, Ü. Güler, I. Vatolkin, and M. Preuss</i>:<b><font color=#0000FF> BeatTheBeat: Music-Based Procedural Content Generation In a Mobile Game</font></b>. Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games (CIG), pp. 320-327, <font color=#996600>2012</font></html>
-<html><b><font color=#006633>[13]</font></b> <i>G. Rötter, I. Vatolkin, and C. Weihs</i>:<b><font color=#0000FF> Computational Prediction of High-Level Descriptors of Music Personal Categories</font></b>. Accepted for Proceedings of the 35th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2011</font></html>
+<html><b><font color=#006633>[c13]</font></b> <i>G. Rötter, I. Vatolkin, and C. Weihs</i>:<b><font color=#0000FF> Computational Prediction of High-Level Descriptors of Music Personal Categories</font></b>. Accepted for Proceedings of the 35th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2011</font></html>
-<html><b><font color=#006633>[12]</font></b> <i>V. Mattern, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> A Case Study about the Effort to Classify Music Intervals by Chroma and Spectrum Analysis</font></b>. Accepted for Proceedings of the 35th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2011</font></html>
+<html><b><font color=#006633>[c12]</font></b> <i>V. Mattern, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> A Case Study about the Effort to Classify Music Intervals by Chroma and Spectrum Analysis</font></b>. Accepted for Proceedings of the 35th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2011</font></html>
-<html><b><font color=#006633>[11]</font></b> <i>T. Deinert, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Regression-Based Tempo Recognition from Chroma and Energy Accents for Slow Audio Recordings</font></b>. Proceedings of the AES 42nd International Conference on Semantic Audio (AES), pp. 60-68, <html><font color=#996600>2011</font></html>
+<html><b><font color=#006633>[c11]</font></b> <i>T. Deinert, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Regression-Based Tempo Recognition from Chroma and Energy Accents for Slow Audio Recordings</font></b>. Proceedings of the AES 42nd International Conference on Semantic Audio (AES), pp. 60-68, <html><font color=#996600>2011</font></html>
-<html><b><font color=#006633>[10]</font></b> <i>I. Vatolkin, M. Preuß, and G. Rudolph</i>:<b><font color=#0000FF> Multi-Objective Feature Selection in Music Genre and Style Recognition Tasks</font></b>. Proceedings of the 2011 Genetic and Evolutionary Computation Conference (GECCO), pp. 411-418, <font color=#996600>2011</font></html>
+<html><b><font color=#006633>[c10]</font></b> <i>I. Vatolkin, M. Preuß, and G. Rudolph</i>:<b><font color=#0000FF> Multi-Objective Feature Selection in Music Genre and Style Recognition Tasks</font></b>. Proceedings of the 2011 Genetic and Evolutionary Computation Conference (GECCO), pp. 411-418, <font color=#996600>2011</font></html>
-<html><b><font color=#006633>[9]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Multi-Objective Evaluation of Music Classification</font></b>. Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2010</font></html>
+<html><b><font color=#006633>[c9]</font></b> <i>I. Vatolkin</i>:<b><font color=#0000FF> Multi-Objective Evaluation of Music Classification</font></b>. Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2010</font></html>
-<html><b><font color=#006633>[8]</font></b> <i>I. Vatolkin, W. Theimer, and M. Botteck</i>:<b><font color=#0000FF> Partition Based Feature Processing for Improved Music Classification</font></b>. Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2010</font></html>
+<html><b><font color=#006633>[c8]</font></b> <i>I. Vatolkin, W. Theimer, and M. Botteck</i>:<b><font color=#0000FF> Partition Based Feature Processing for Improved Music Classification</font></b>. Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2010</font></html>
-<html><b><font color=#006633>[7]</font></b> <i>C. Weihs, K. Friedrichs, M. Eichhoff, and I. Vatolkin</i>:<b><font color=#0000FF> Software in Music Information Retrieval (MIR)</font></b>. Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2010</font></html>
+<html><b><font color=#006633>[c7]</font></b> <i>C. Weihs, K. Friedrichs, M. Eichhoff, and I. Vatolkin</i>:<b><font color=#0000FF> Software in Music Information Retrieval (MIR)</font></b>. Proceedings of the 34th Annual Conference of the German Classification Society (GfKl), <font color=#996600>2010</font></html>
-<html><b><font color=#006633>[6]</font></b> <i>A. Nagathil, I. Vatolkin, and W. Theimer</i>:<b><font color=#0000FF> Comparison of Partition-Based Audio Features for Music Classification</font></b>. Proceedings the 9th ITG Fachtagung Sprachkommunikation, <font color=#996600>2010</font></html>
+<html><b><font color=#006633>[c6]</font></b> <i>A. Nagathil, I. Vatolkin, and W. Theimer</i>:<b><font color=#0000FF> Comparison of Partition-Based Audio Features for Music Classification</font></b>. Proceedings the 9th ITG Fachtagung Sprachkommunikation, <font color=#996600>2010</font></html>
-<html><b><font color=#006633>[5]</font></b> <i>B. Bischl, I. Vatolkin and M. Preuß</i>:<b><font color=#0000FF> Selecting Small Audio Feature Sets in Music Classification by Means of Asymmetric Mutation</font></b>. Proceedings of the 11th International Conference on Parallel Problem Solving From Nature (PPSN), pp. 314-323, <font color=#996600>2010</font></html>
+<html><b><font color=#006633>[c5]</font></b> <i>B. Bischl, I. Vatolkin and M. Preuß</i>:<b><font color=#0000FF> Selecting Small Audio Feature Sets in Music Classification by Means of Asymmetric Mutation</font></b>. Proceedings of the 11th International Conference on Parallel Problem Solving From Nature (PPSN), pp. 314-323, <font color=#996600>2010</font></html>
-<html><b><font color=#006633>[4]</font></b> <i>I. Vatolkin, W. Theimer, and M.Botteck</i>:<b><font color=#0000FF> AMUSE (Advanced MUSic Explorer) – A Multitool Framework for Music Data Analysis</font></b>. Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR), pp. 33-38, <font color=#996600>2010</font></html>
+<html><b><font color=#006633>[c4]</font></b> <i>I. Vatolkin, W. Theimer, and M.Botteck</i>:<b><font color=#0000FF> AMUSE (Advanced MUSic Explorer) – A Multitool Framework for Music Data Analysis</font></b>. Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR), pp. 33-38, <font color=#996600>2010</font></html>
-<html><b><font color=#006633>[3]</font></b> <i>I. Vatolkin, W. Theimer, and G. Rudolph</i>:<b><font color=#0000FF> Design and Comparison of Different Evolution Strategies for Feature Selection and Consolidation in Music Classification</font></b>. Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC), pp. 174-181, <font color=#996600>2009</font></html>
+<html><b><font color=#006633>[c3]</font></b> <i>I. Vatolkin, W. Theimer, and G. Rudolph</i>:<b><font color=#0000FF> Design and Comparison of Different Evolution Strategies for Feature Selection and Consolidation in Music Classification</font></b>. Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC), pp. 174-181, <font color=#996600>2009</font></html>
-<html><b><font color=#006633>[2]</font></b> <i>I. Vatolkin and W. Theimer</i>:<b><font color=#0000FF> Optimization of Feature Processing Chain in Music Classification by Evolutionary Strategies</font></b>. Proceedings of the 10th International Conference on Parallel Problem Solving from Nature (PPSN), pp. 1150-1159, <font color=#996600>2008</font></html>
+<html><b><font color=#006633>[c2]</font></b> <i>I. Vatolkin and W. Theimer</i>:<b><font color=#0000FF> Optimization of Feature Processing Chain in Music Classification by Evolutionary Strategies</font></b>. Proceedings of the 10th International Conference on Parallel Problem Solving from Nature (PPSN), pp. 1150-1159, <font color=#996600>2008</font></html>
-<html><b><font color=#006633>[1]</font></b> <i>W. Theimer, I. Vatolkin, M. Botteck, and M. Buchmann</i>:<b><font color=#0000FF> Content-Based Similarity Search and Visualization for Personal Music Categories</font></b>. Proceedings of the 6th International Workshop on Content-Based Multimedia Indexing (CBMI), pp. 9-16, <font color=#996600>2008</font></html>
+<html><b><font color=#006633>[c1]</font></b> <i>W. Theimer, I. Vatolkin, M. Botteck, and M. Buchmann</i>:<b><font color=#0000FF> Content-Based Similarity Search and Visualization for Personal Music Categories</font></b>. Proceedings of the 6th International Workshop on Content-Based Multimedia Indexing (CBMI), pp. 9-16, <font color=#996600>2008</font></html>
 ===== PhD =====
-<html><b><font color=#006633>[1]</font></b> <i>I. Vatolkin</i>: <b><a href="https://eldorado.tu-dortmund.de/bitstream/2003/30402/1/Dissertation.pdf"><font color=#0000FF>Improving Supervised Music Classification by Means of Multi-Objective Evolutionary Feature Selection</font></a></b>. Department of Computer Science, TU Dortmund <font color=#996600>2013</font></html>
+<html><b><font color=#006633>[p1]</font></b> <i>I. Vatolkin</i>: <b><a href="https://eldorado.tu-dortmund.de/bitstream/2003/30402/1/Dissertation.pdf"><font color=#0000FF>Improving Supervised Music Classification by Means of Multi-Objective Evolutionary Feature Selection</font></a></b>. Department of Computer Science, TU Dortmund <font color=#996600>2013</font></html>
 ===== Technical Reports =====
-<html><b><font color=#006633>[3]</font></b> <i>I. Vatolkin, M. Preuß, and G. Rudolph</i>: <b><a href="http://ls11-www.cs.tu-dortmund.de/_media/techreports/tr13-01.pdf"><font color=#0000FF>Training Set Reduction Based on 2-Gram Feature Statistics for Music Genre Recognition</font></a></b>. Technical Report TR13-2-001, Chair of Algorithm Engineering, TU Dortmund, presented at the 2012 Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML), <font color=#996600>2013</font></html>
+<html><b><font color=#006633>[tr3]</font></b> <i>I. Vatolkin, M. Preuß, and G. Rudolph</i>: <b><a href="http://ls11-www.cs.tu-dortmund.de/_media/techreports/tr13-01.pdf"><font color=#0000FF>Training Set Reduction Based on 2-Gram Feature Statistics for Music Genre Recognition</font></a></b>. Technical Report TR13-2-001, Chair of Algorithm Engineering, TU Dortmund, presented at the 2012 Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML), <font color=#996600>2013</font></html>
-<html><b><font color=#006633>[2]</font></b> <i>W. Theimer, I. Vatolkin, and A. Eronen</i>: <b><a href="/people/vatol/publications/PDFs/TR08_2_001.pdf"><font color=#0000FF>Definitions of Audio Features for Music Content Description</font></a></b>. Technical Report TR08-2-001, Chair of Algorithm Engineering, University of Dortmund, <font color=#996600>2008</font></html>
+<html><b><font color=#006633>[tr2]</font></b> <i>W. Theimer, I. Vatolkin, and A. Eronen</i>: <b><a href="/people/vatol/publications/PDFs/TR08_2_001.pdf"><font color=#0000FF>Definitions of Audio Features for Music Content Description</font></a></b>. Technical Report TR08-2-001, Chair of Algorithm Engineering, University of Dortmund, <font color=#996600>2008</font></html>
-<html><b><font color=#006633>[1]</font></b> <i>I. Vatolkin and W. Theimer</i>: <b><a href="/people/vatol/publications/PDFs/NRC-TR-2007-012.pdf"><font color=#0000FF>Introduction to Methods for Music Classification Based on Audio Data</font></a></b>. Nokia Research Center Technical Report NRC-TR-2007-012, <font color=#996600>2007</font></html>
+<html><b><font color=#006633>[tr1]</font></b> <i>I. Vatolkin and W. Theimer</i>: <b><a href="/people/vatol/publications/PDFs/NRC-TR-2007-012.pdf"><font color=#0000FF>Introduction to Methods for Music Classification Based on Audio Data</font></a></b>. Nokia Research Center Technical Report NRC-TR-2007-012, <font color=#996600>2007</font></html>

Chair 11

Teaching

Research Groups

Differences