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Towards recognizing "cool": can end users help computer vision recognize subjective attributes of objects in images?

, , , , , , , and . IUI, page 285-288. ACM, (2012)

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The Quantile Snapshot Scan: Comparing Quantiles of Spatial Data from Two Snapshots in Time., and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 2677-2686. PMLR, (2020)Discovering Hotspots and Coldspots of Species Richness in eBird Data., and . AAAI Workshop: Computational Sustainability, volume WS-15-06 of AAAI Technical Report, AAAI Press, (2015)Explanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs., , , , , , , , and . VL/HCC, page 41-48. IEEE Computer Society, (2010)End-user feature labeling: Supervised and semi-supervised approaches based on locally-weighted logistic regression., , , , , , and . Artif. Intell., (2013)End-User Feature Labeling via Locally Weighted Logistic Regression., , , , , , and . AAAI, page 1575-1578. AAAI Press, (2011)End-user feature labeling: a locally-weighted regression approach., , , , , , and . IUI, page 115-124. ACM, (2011)Towards recognizing "cool": can end users help computer vision recognize subjective attributes of objects in images?, , , , , , , and . IUI, page 285-288. ACM, (2012)An Efficient Quantile Spatial Scan Statistic for Finding Unusual Regions in Continuous Spatial Data with Covariates., and . UAI, page 756-765. AUAI Press, (2018)Coalition-Committees as Network Interventions: Baseline Network Composition in Context of Childhood Obesity Prevention Interventions., , , , , and . Syst., 9 (3): 66 (2021)