Biblio
Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy Models. ACM Transactions on Knowledge Discovery from Data. 2018;12(1). paper.pdf (7.13 MB)
. Observation-Level and Parametric Interaction for High-Dimensional Data Analysis. ACM Transactions on Interactive Intelligent Systems. 2018;8(2). observation-level-parametric_first_look_version.pdf (1.82 MB)
. SIRIUS: Dual, Symmetric, Interactive Dimension Reductions. In: 2018 IEEE Conference on Visual Analytics Science and Technology (VAST). 2018 IEEE Conference on Visual Analytics Science and Technology (VAST). ; 2018. p. . SIRIUS 2018 v3 preprint sm.pdf (470.59 KB) SIRIUS 2018 Comparisions v3 preprint.pdf (87.44 KB)
. Smooth, Efficient, and Interruptible Zooming and Panning. IEEE Transactions on Visualization & Computer Graphics . 2018. 1801.09358.pdf (1.26 MB)
. Towards a Systematic Combination of Dimension Reduction and Clustering in Visual Analytics. IEEE Transactions on Visualization and Computer Graphics. 2018;24:131-141. systematic-combination-dimension.pdf (6 MB)
. Albireo: An Interactive Tool for Visually Summarizing Computational Notebook Structure. In: 2019 Symposium on Visualization in Data Science (VDS’19). 2019 Symposium on Visualization in Data Science (VDS’19). ; 2019. p. . Albireo__Visualizing_Computational_Notebooks.pdf (984.33 KB)
. DeepVA: Bridging Cognition and Computation through Semantic Interaction and Deep Learning. In: Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. . Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. . ; 2019. p. . MLUI_2019-2.pdf (8.51 MB)
. Dropping the Baton?: Understanding Errors and Bottlenecks in a Crowdsourced Sensemaking Pipeline. Proc. ACM Hum.-Comput. Interact. [Internet]. 2019;3:136:1–136:26. Available from: http://doi.acm.org/10.1145/3359238 cscw136-li.pdf (2.09 MB)
. The Effect of Edge Bundling and Seriation on Sensemaking of Biclusters in Bipartite Graphs. IEEE Transactions on Visualization and Computer Graphics. 2019;25(10):2983-2998. 08423100.pdf (5.86 MB)
. Evaluating Semantic Interaction on Word Embeddings via Simulation. In: EValuation of Interactive VisuAl Machine Learning systems, an IEEE VIS 2019 Workshop. EValuation of Interactive VisuAl Machine Learning systems, an IEEE VIS 2019 Workshop. ; 2019. p. . sub1013.pdf (786.6 KB)
. Immersive Analytics: Theory and Research Agenda. Frontiers in Robotics and AI [Internet]. 2019;6:82. Available from: https://www.frontiersin.org/article/10.3389/frobt.2019.00082 92e73d798fc9ef4c3da4c542606c9a38f337.pdf (2.79 MB)
. Intelligent Systems for Geosciences: An Essential Research Agenda. COMMUNICATIONS OF THE ACM. 2019;62(1):76-84. CACM-IS-GEO-2018.pdf (3.02 MB)
. Interactive Bicluster Aggregation in Bipartite Graphs. In: VIS 2019 Short Papers. VIS 2019 Short Papers. ; 2019. p. .
. Interactive Visual Analytics for Sensemaking with Big Text. Big Data Research [Internet]. 2019;16:49 - 58. Available from: http://www.sciencedirect.com/science/article/pii/S2214579618302995 1-s2.0-S2214579618302995-main.pdf (1.32 MB)
. Machine Learning from Interaction in Multi-Model Visual Analytics. In: Proceedings of the ACM CHI Conference Workshop on Human-Centered Machine Learning Perspectives at CHI’19. Proceedings of the ACM CHI Conference Workshop on Human-Centered Machine Learning Perspectives at CHI’19. ; 2019. p. . HCML_Submission.pdf (552.21 KB)
. Machine Learning from User Interaction for Visualization and Analytics: A Workshop-Generated Research Agenda. In: Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. ; 2019. p. . MLUI_Long_Paper.pdf (5.22 MB)
. Pollux: Interactive Cluster-First Projections of High-Dimensional Data. In: 2019 Symposium on Visualization in Data Science (VDS’19). 2019 Symposium on Visualization in Data Science (VDS’19). ; 2019. p. . The_Pollux_Paper-2.pdf (1.8 MB)
. Simultaneous Interaction with Dimension Reduction and Clustering Projections. In: Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion. Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion. New York, NY, USA; 2019. p. 89–90. Available from: http://doi.acm.org/10.1145/3308557.3308718 p89-wenskovitch.pdf (478.5 KB)
. Towards insight-driven sampling for big data visualisation. Behaviour & Information Technology [Internet]. 2019:1-20. Available from: https://doi.org/10.1080/0144929X.2019.1616223 Towards insight driven sampling for big data visualisation.pdf (2.84 MB)
. Uncertainty in Interactive WMDS Visualizations. 2019 Symposium on Visualization in Data Science Posters. 2019. uncertainty-in-wmds-vds.pdf (355.18 KB)
. Auto-Grading Jupyter Notebooks. In: SIGCSE 2020. SIGCSE 2020. ; 2020. p. . Auto_Grading_Jupyter_Notebooks.pdf (735.01 KB)
. Challenges in Evaluating Interactive Visual Machine Learning Systems. IEEE Computer Graphics and Applications. 2020;40(6):88-96.
. CrowdTrace: Visualizing Provenance in Distributed Sensemaking. In: IEEE VIS Short Papers. IEEE VIS Short Papers. ; 2020. p. 5 pages. CrowdTrace_VIS_Short_Paper_Submission-3.pdf (738.58 KB)
. Evaluating the Benefits of the Immersive Space to Think. In: IEEE 6th Workshop on Everyday Virtual Reality (WEVR). IEEE 6th Workshop on Everyday Virtual Reality (WEVR). ; 2020. p. . WEVR2020_Lisle.pdf (4.23 MB)
. Immersive Space to Think: The Role of 3D Space for Sensemaking. In: 4th Workshop on Immersive Analytics at ACM CHI 2020. 4th Workshop on Immersive Analytics at ACM CHI 2020. ; 2020. p. 8 . 03_submission3-CHI2020_IA.pdf (1.63 MB)
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