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Items where Author is "Wong, W-K"

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Number of items: 6.

Article

Groce, A., Kulesza, T., Zhang, C. , Shamasunder, S., Burnett, M., Wong, W-K, Stumpf, S., Das, S., Shinsel, A., Bice, F. & McIntosh, K. (2014). You are the only possible oracle: Effective test selection for end users of interactive machine learning systems. IEEE Transactions on Software Engineering, 40(3), pp. 307-323. doi: 10.1109/tse.2013.59

Das, S., Moore, T., Wong, W-K , Stumpf, S., Oberst, I., McIntosh, K. & Burnett, M. (2013). End-user feature labeling: Supervised and semi-supervised approaches based on locally-weighted logistic regression. Artificial Intelligence, 204, pp. 56-74. doi: 10.1016/j.artint.2013.08.003

Kulesza, T., Stumpf, S., Burnett, M. , Yang, S., Kwan, I. & Wong, W-K (2013). Too much, too little, or just right? Ways explanations impact end users' mental models. Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC, pp. 3-10. doi: 10.1109/VLHCC.2013.6645235

Book Section

Stumpf, S., Burnett, M., Pipek, V. & Wong, W-K (2012). End-user interactions with intelligent and autonomous systems. In: Konstan, J. A., Chi, E. H. & Höök, K. (Eds.), CHI '12 Extended Abstracts on Human Factors in Computing Systems. (pp. 2755-2758). New York: ACM. doi: 10.1145/2212776.2212713

Curran, W., Moore, T., Kulesza, T. , Wong, W-K, Todorovic, S., Stumpf, S., White, R. & Burnett, M. (2012). Towards recognizing "cool": can end users help computer vision recognize subjective attributes of objects in images? In: Duarte, C., Carriço, L., Jorge, J. A. , Oviatt, S. L. & Gonçalves, D. (Eds.), Proceedings of the 2012 ACM international conference on Intelligent User Interfaces. (pp. 285-288). New York: ACM. doi: 10.1145/2166966.2167019

Wong, W-K, Oberst, I., Das, S. , Moore, T., Stumpf, S., McIntosh, K. & Burnett, M. (2011). End-user feature labeling: a locally-weighted regression approach. In: Pu, P., Pazzani, M. J., André, E. & Riecken, D. (Eds.), Proceedings of the 16th international conference on Intelligent user interfaces. (pp. 115-124). New York: ACM. doi: 10.1145/1943403.1943423

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