G. Albuquerque, M. Eisemann, and M. Magnor, Perception-based visual quality measures, 2011 IEEE Conference on Visual Analytics Science and Technology (VAST), pp.13-20, 2011.
DOI : 10.1109/VAST.2011.6102437

W. Banzhaf, Handbook of Evolutionary Computation, chapter Interactive Evolution, 1997.

M. Behrisch, F. Korkmaz, L. Shao, and T. Schreck, Feedback-driven interactive exploration of large multidimensional data supported by visual classifier, 2014 IEEE Conference on Visual Analytics Science and Technology (VAST), 2014.
DOI : 10.1109/VAST.2014.7042480

E. Bertini, A. Tatu, and D. Keim, Quality Metrics in High-Dimensional Data Visualization: An Overview and Systematization, IEEE Transactions on Visualization and Computer Graphics, vol.17, issue.12, pp.172203-2212, 2011.
DOI : 10.1109/TVCG.2011.229

A. Bezerianos, F. Chevalier, P. Dragicevic, N. Elmqvist, and J. Fekete, GraphDice: A System for Exploring Multivariate Social Networks, Proc. EuroVis, pp.29863-872, 2010.
DOI : 10.1111/j.1467-8659.2009.01687.x
URL : https://hal.archives-ouvertes.fr/inria-00521661

N. Boukhelifa, C. Ticona, W. G. Bezerianos, A. Lutton, and E. , Evolutionary Visual Exploration: Evaluation With Expert Users, Computer Graphics Forum, vol.17, issue.2, pp.3231-3271, 2013.
DOI : 10.1111/cgf.12090
URL : https://hal.archives-ouvertes.fr/hal-00805234

E. Brown, J. Liu, C. Brodley, C. , and R. , Dis-function: Learning distance functions interactively, 2012 IEEE Conference on Visual Analytics Science and Technology (VAST), pp.83-92, 2012.
DOI : 10.1109/VAST.2012.6400486

E. T. Brown, J. Liu, C. E. Brodley, C. , and R. , Dis-function: Learning distance functions interactively, 2012 IEEE Conference on Visual Analytics Science and Technology (VAST), pp.83-92, 2012.
DOI : 10.1109/VAST.2012.6400486

E. T. Brown, A. Ottley, H. Zhao, Q. Lin, R. Souvenir et al., Finding Waldo: Learning about Users from their Interactions, IEEE Transactions on Visualization and Computer Graphics, vol.20, issue.12, p.991, 2014.
DOI : 10.1109/TVCG.2014.2346575

S. K. Card, J. D. Mackinlay, and B. Shneiderman, Readings in Information Visualization: Using Vision to Think, 1999.

S. Carpendale, Evaluating Information Visualizations, Information Visualization, pp.19-45, 2008.
DOI : 10.1007/978-3-540-70956-5_2

C. Chen, Top 10 Unsolved Information Visualization Problems, IEEE Computer Graphics and Applications, vol.25, issue.4, pp.12-16, 2005.
DOI : 10.1109/MCG.2005.91

M. Chen and H. Hagen, Guest Editors' Introduction: Knowledge-Assisted Visualization, IEEE Computer Graphics and Applications, vol.30, issue.1, pp.15-16, 2010.
DOI : 10.1109/MCG.2010.8

T. N. Dang and L. Wilkinson, Scagexplorer: Exploring scatterplots by their scagnostics, Proceedings of the 2014 IEEE Pacific Visualization Symposium, PACIFICVIS '14, pp.73-80, 2014.

N. Elmqvist, P. Dragicevic, and J. Fekete, Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation, Proc. InfoVis, pp.141141-1148, 2008.
DOI : 10.1109/TVCG.2008.153
URL : https://hal.archives-ouvertes.fr/hal-00699065

A. Endert, P. Fiaux, and C. North, Unifying the sensemaking loop with semantic interaction, IEEE Workshop on Interactive Visual Text Analytics for Decision Making at VisWeek 2011, 2011.

A. Endert, P. Fiaux, and C. North, Semantic interaction for visual text analytics, Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems, CHI '12, pp.473-482, 2012.
DOI : 10.1145/2207676.2207741

S. J. Fernstad, J. Shaw, and J. Johansson, Quality-based guidance for exploratory dimensionality reduction, Information Visualization, vol.13, issue.1, pp.44-64, 2013.
DOI : 10.1038/nmeth.f.303

G. Fischer, User modeling in human&computer interaction, User Modeling and User-Adapted Interaction, vol.11, issue.1/2, pp.65-86, 2001.
DOI : 10.1023/A:1011145532042

M. Fukumoto, S. Ogawa, S. Nakashima, and J. Ichi-imai, Extended Interactive Evolutionary Computation using heart rate variability as fitness value for composing music chord progression, 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC), pp.407-412, 2010.
DOI : 10.1109/NABIC.2010.5716344

G. G. Grinstein, Harnessing the human in knowledge discovery, KDD, pp.384-385, 1996.

A. Guettala, F. Bouali, C. Guinot, and G. Venturini, A User Assistant for the Selection and Parameterization of the Visualizations in Visual Data Mining, 2012 16th International Conference on Information Visualisation, pp.252-257, 2012.
DOI : 10.1109/IV.2012.50
URL : https://hal.archives-ouvertes.fr/hal-01024588

N. Hayashida and H. Takagi, Visualized IEC: interactive evolutionary computation with multidimensional data visualization, 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies and Industrial Opportunities (Cat. No.00CH37141), pp.2738-2743, 2000.
DOI : 10.1109/IECON.2000.972431

S. Ingram, T. Munzner, V. Irvine, M. Tory, S. Bergner et al., DimStiller: Workflows for dimensional analysis and reduction, 2010 IEEE Symposium on Visual Analytics Science and Technology, pp.3-10, 2010.
DOI : 10.1109/VAST.2010.5652392

S. Johansson and J. Johansson, Interactive dimensionality reduction through user-defined combinations of quality metrics. Visualization and Computer Graphics, IEEE Transactions on, vol.15, issue.6, pp.993-1000, 2009.

J. R. Koza, Genetic Programming, 1992.

S. Leman, L. House, D. Maiti, A. Endert, and C. North, Visual to Parametric Interaction (V2PI), PLoS ONE, vol.11, issue.3, p.50474, 2013.
DOI : 10.1371/journal.pone.0050474.s001

X. Llorà, K. Sastry, F. Alías, D. E. Goldberg, and M. Welge, Analyzing active interactive genetic algorithms using visual analytics, Proceedings of the 8th annual conference on Genetic and evolutionary computation , GECCO '06, pp.1417-1418, 2006.
DOI : 10.1145/1143997.1144223

E. Lutton, EVOLUTION OF FRACTAL SHAPES FOR ARTISTS AND DESIGNERS, International Journal on Artificial Intelligence Tools, vol.15, issue.04, pp.651-672, 2006.
DOI : 10.1142/S0218213006002850

E. Lutton, M. Pilz, L. Véhel, and J. , The Fitness Map Scheme. Application to interactive multifractal image denoising., 2005 IEEE Congress on Evolutionary Computation, 2005.
DOI : 10.1109/CEC.2005.1554978
URL : https://hal.archives-ouvertes.fr/hal-00539352

W. E. Mackay, Responding to cognitive overhead: co-adaptation between users and technology, Intellectica, vol.30, issue.1, pp.177-193, 2000.

S. Malinchik and E. Bonabeau, Exploratory Data Analysis with Interactive Evolution, Genetic and Evolutionary Computation GECCO 2004, pp.1151-1161, 2004.
DOI : 10.1007/978-3-540-24855-2_124

K. Matkovic, D. Gracanin, M. Jelovic, and H. Hauser, Interactive Visual Steering - Rapid Visual Prototyping of a Common Rail Injection System, IEEE Transactions on Visualization and Computer Graphics, vol.14, issue.6, 2008.
DOI : 10.1109/TVCG.2008.145

K. Matkovic, D. Gracanin, M. Jelovic, and H. Hauser, Interactive visual analysis supporting design , tuning, and optimization of diesel engine injection, 2011.

O. J. Mengshoel and D. E. Goldberg, The Crowding Approach to Niching in Genetic Algorithms, Evolutionary Computation, vol.4, issue.3, pp.315-354, 2008.
DOI : 10.1109/21.370197

M. Meyer, M. Sedlmair, and T. Munzner, The four-level nested model revisited, Proceedings of the 2012 BELIV Workshop on Beyond Time and Errors, Novel Evaluation Methods for Visualization, BELIV '12, 2012.
DOI : 10.1145/2442576.2442587

J. A. Mouradian, B. Hamann, and R. Rosenbaum, A general approach for similarity-based linear projections using a genetic algorithm, Proceedings of SPIE, pp.82940-82940, 2012.

J. E. Nam and K. Mueller, TripAdvisor^{N-D}: A Tourism-Inspired High-Dimensional Space Exploration Framework with Overview and Detail, IEEE Transactions on Visualization and Computer Graphics, vol.19, issue.2, pp.291-305, 2013.
DOI : 10.1109/TVCG.2012.65

W. Peng, M. O. Ward, and E. A. Rundensteiner, Clutter reduction in multi-dimensional data visualization using dimension reordering, Proceedings of the IEEE Symposium on Information Visualization, INFOVIS '04, pp.89-96, 2004.

A. Perer and B. Shneiderman, Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines, IEEE Computer Graphics and Applications, vol.29, issue.3, pp.2939-51, 2009.
DOI : 10.1109/MCG.2009.44

T. Pham, R. Hess, C. Ju, E. Zhang, and R. A. Metoyer, Visualization of Diversity in Large Multivariate Data Sets, IEEE Transactions on Visualization and Computer Graphics, vol.16, issue.6, pp.1053-1062, 2010.
DOI : 10.1109/TVCG.2010.216

R. Poli and S. Cagnoni, Genetic programming with user-driven selection: Experiments on the evolution of algorithms for image enhancement, Genetic Programming 1997: Proceedings of the Second Annual Conference, pp.269-277, 1997.

R. A. Rensink and G. Baldridge, The Perception of Correlation in Scatterplots, Computer Graphics Forum, vol.2, issue.2, pp.1203-1210, 2010.
DOI : 10.1111/j.1467-8659.2009.01694.x

P. Saraiya, C. North, and K. Duca, An Insight-Based Methodology for Evaluating Bioinformatics Visualizations, IEEE Transactions on Visualization and Computer Graphics, vol.11, issue.4, pp.443-456, 2005.
DOI : 10.1109/TVCG.2005.53

M. Sedlmair, C. Heinzl, S. Bruckner, H. Piringer, and T. Moller, Visual parameter space analysis: A conceptual framework. Visualization and Computer Graphics, IEEE Transactions on, issue.99, pp.1-1, 2014.

M. Sedlmair, M. Meyer, and T. Munzner, Design Study Methodology: Reflections from the Trenches and the Stacks, Proc. InfoVis), pp.182431-2440, 2012.
DOI : 10.1109/TVCG.2012.213

J. Seo and B. Shneiderman, A Rank-by-Feature Framework for Interactive Exploration of Multidimensional Data, Information Visualization, vol.43, issue.2, pp.99-113, 2005.
DOI : 10.1057/palgrave.ivs.9500091

C. E. Shannon, A mathematical theory of communication. The Bell System Technical Journal, pp.379-423, 1948.

L. Shao, M. Behrisch, T. Schreck, T. Von-landesberger, M. Scherer et al., Guided Sketching for Visual Search and Exploration in Large Scatter Plot Spaces, Proc. EuroVA International Workshop on Visual Analytics, 2014.

I. Smith, A tutorial on principal component analysis, 2002.

C. D. Stolper, A. Perer, and D. Gotz, Progressive Visual Analytics: User-Driven Visual Exploration of In-Progress Analytics, IEEE Transactions on Visualization and Computer Graphics, vol.20, issue.12, pp.1653-1662, 2014.
DOI : 10.1109/TVCG.2014.2346574

H. Takagi, Interactive evolutionary computation, IEEE Int. Conf. on Intelligent Engineering Systems (INES'98), 1998.
DOI : 10.1007/BF03037488

H. Takagi, Interactive evolutionary computation, New Generation Computing, vol.23, issue.2, p.98, 1998.
DOI : 10.1007/BF03037488

J. J. Thomas and K. A. Cook, Illuminating the Path: The Research and Development Agenda for Visual Analytics, National Visualization and Analytics Ctr, 2005.

W. C. Ticona, N. Boukhelifa, A. Bezerianos, and E. Lutton, Evolutionary visual exploration: experimental analysis of algorithm behaviour, GECCO (Companion), pp.1373-1380, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00818641

C. Turkay, F. Jeanquartier, A. Holzinger, and H. Hauser, On Computationally-Enhanced Visual Analysis of Heterogeneous Data and Its Application in Biomedical Informatics, Interactive Knowledge Discovery and Data Mining in Biomedical Informatics -State-of-the-Art and Future Challenges, pp.117-140, 2014.
DOI : 10.1145/1541880.1541882

L. Wilkinson and G. Wills, Scagnostics Distributions, Journal of Computational and Graphical Statistics, vol.17, issue.2, pp.473-491, 2008.
DOI : 10.1198/106186008X320465