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We present a new stage-wise learning paradigm for training generative adversarial networks (GANs).
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Nguyen, X., Wainwright, M.J., Jordan, M.I.: On information divergence measures, surrogate loss functions and decentralized hypothesis testing. Department of EECS and Department of Statistics UC Berkeley, CA (2005)
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Nguyen, X., Wainwright, M.J., Jordan, M.I.: On surrogate loss functions and f-divergences. The Annals of Statistics pp. 876–904 (2009)
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Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: NIPS. pp. 2672–2680 (2014)
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Juefei-Xu, F., Pal, D.K., Savvides, M.: Hallucinating the Full Face from the Periocular Region via Dimensionally Weighted K-SVD. In: CVPRW. pp. 1–8 (June 2014)
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Denton, E.L., Chintala, S., Fergus, R., et al.: Deep generative image models using a laplacian pyramid of adversarial networks. In: NIPS. pp. 1486–1494 (2015)
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Juefei-Xu, F., Luu, K., Savvides, M.: Spartans: Single-sample Periocular-based Alignment-robust Recognition Technique Applied to Non-frontal Scenarios. IEEE TIP 24
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Juefei-Xu, F., Pal, D.K., Savvides, M.: NIR-VIS Heterogeneous Face Recognition via Cross-Spectral Joint Dictionary Learning and Reconstruction. In: CVPRW. pp. 141–150 (June 2015)
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Juefei-Xu, F., Pal, D.K., Singh, K., Savvides, M.: A Preliminary Investigation on the Sensitivity of COTS Face Recognition Systems to Forensic Analyst-style Face Processing for Occlusions. In: CVPRW. pp. 25–33 (June 2015)
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Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: ICCV (December 2015)
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Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., Chen, X.: Improved techniques for training gans. In: NIPS. pp. 2226–2234 (2016)
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Amos, B., Bartosz, L., Satyanarayanan, M.: Openface: A general-purpose face recognition library with mobile applications. Tech. rep., CMU-CS-16-118, CMU School of Computer Science (2016)
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Juefei-Xu, F., Savvides, M.: Fastfood Dictionary Learning for Periocular-Based Full Face Hallucination. In: BTAS. pp. 1–8 (Sept 2016)
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Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein GAN. arXiv preprint arXiv:1701.07875 (2017)
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Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.C.: Improved training of wasserstein gans. In: NIPS. pp. 5769–5779 (2017)
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Yang, J., Kannan, A., Batra, B., Parikh, D.: Lr-gan - layered recursive generative adversarial networks for image generation. ICLR (under review) (2017)
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