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While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge.
Learning question classifiers
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Opening the black box: Data driven visualization of neural networks
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Visualizing data using t-SNE
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Investigating statistical machine learning as a tool for software development
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Theano: A CPU and GPU math expression compiler
J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian, D. Warde-Farley, and Y. Bengio · 2010
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iVisClassifier: An interactive visual analytics system for classification based on supervised dimension reduction
J. Choo, H. Lee, J. Kihm, and H. Park · 2010
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Gestalt: Integrated support for implementation and analysis in machine learning
K. Patel, N. Bancroft, S. M. Drucker, J. Fogarty, A. J. Ko, and J. Landay · 2010
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Why-oriented end-user debugging of naive Bayes text classification
T. Kulesza, S. Stumpf, W.-K. Wong, M. M. Burnett, S. Perona, A. Ko, and I. Oberst · 2011
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BaobabView: Interactive construction and analysis of decision trees
S. Van Den Elzen and J. J. Van Wijk · 2011
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Explainers: Expert explorations with crafted projections
M. Gleicher · 2013
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Ad click prediction: A view from the trenches
H. B. McMahan, G. Holt, D. Sculley, M. Young, D. Ebner, J. Grady, L. Nie, T. Phillips, E. Davydov, D. Golovin, S. Chikkerur, D. Liu, M. Wattenberg, A. M. Hrafnkelsson, T. Boulos, and J. Kubica · 2013
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Practical lessons from predicting clicks on ads at Facebook
X. He, J. Pan, O. Jin, T. Xu, B. Liu, T. Xu, Y. Shi, A. Atallah, R. Herbrich, S. Bowers, and J. Q. Candela · 2014
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Convolutional neural networks for sentence classification
Y. Kim · 2014
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Infuse: Interactive feature selection for predictive modeling of high dimensional data
J. Krause, A. Perer, and E. Bertini · 2014
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ModelTracker: Redesigning performance analysis tools for machine learning
S. Amershi, M. Chickering, S. M. Drucker, B. Lee, P. Simard, and J. Suh · 2015
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FeatureInsight: Visual support for error-driven feature ideation in text classification
M. Brooks, S. Amershi, B. Lee, S. M. Drucker, A. Kapoor, and P. Simard · 2015
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An interactive node-link visualization of convolutional neural networks
A. W. Harley · 2015
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Principles of explanatory debugging to personalize interactive machine learning
T. Kulesza, M. Burnett, W.-K. Wong, and S. Stumpf · 2015
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TensorFlow: Large-scale machine learning on heterogeneous distributed systems
Supporting iterative cohort construction with visual temporal queries
J. Krause, A. Perer, and H. Stavropoulos · 2016
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Why should I trust you?: Explaining the predictions of any classifier
M. T. Ribeiro, S. Singh, and C. Guestrin · 2016
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Direct-manipulation visualization of deep networks
D. Smilkov, S. Carter, D. Sculley, F. B. Viegas, and M. Wattenberg · 2016
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Embedding Projector: Interactive visualization and interpretation of embeddings
D. Smilkov, N. Thorat, C. Nicholson, E. Reif, F. B. Viégas, and M. Wattenberg · 2016
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Understanding neural networks through deep visualization
J. Yosinski, J. Clune, A. Nguyen, T. Fuchs, and H. Lipson · 2016
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M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin, S. Ghemawat, I. Goodfellow, A. Harp, G. Irving, M. Isard, Y. Jia, R. Jozefowicz, L. Kaiser, M. Kudlur, J. Levenberg, D. Mané, R. Monga, S. Moore, D. Murray, C. Olah, M. Schuster, J. Shlens, B. Steiner, I. Sutskever, K. Talwar, P. Tucker, V. Vanhoucke, V. Vasudevan, F. Viégas, O. Vinyals, P. Warden, M. Wattenberg, M. Wicke, Y. Yu, and X. Zheng · 2016
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Productionizing machine learning pipelines at scale
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Serving a billion personalized news feeds
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Deep neural networks for YouTube recommendations
P. Covington, J. Adams, and E. Sargin · 2016
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Bag of tricks for efficient text classification
A. Joulin, E. Grave, P. Bojanowski, and T. Mikolov · 2016
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Visual exploration of machine learning results using data cube analysis
M. Kahng, D. Fang, and D. H. P. Chau · 2016
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A. Abdulkader, A. Lakshmiratan, and J. Zhang · 2017
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Implementing a CNN for text classification in TensorFlow
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Convnetjs
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Towards better analysis of deep convolutional neural networks
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Visualizing the hidden activity of artificial neural networks
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