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This work addresses fair generative models.
Analyzing and Improving the Image Quality of StyleGAN
Karras, T.; Laine, S.; Aittala, M.; Hellsten, J.; Lehtinen, J.; and Aila, T. 2020 · 1912
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Freeze the Discriminator: A Simple Baseline for Fine-Tuning GANs
Mo, S.; Cho, M.; and Shin, J. 2020 · 2002
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Understanding and improving information transfer in multi-task learning
Wu, S.; Zhang, H. R.; and Ré, C. 2020 · 2005
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Cong, Y.; Zhao, M.; Li, J.; Wang, S.; and Carin, L. 2020 · 2006
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A survey on transfer learning
Pan, S. J.; and Yang, Q. 2009 · 2009
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Improving the Fairness of Deep Generative Models without Retraining
Tan, S.; Shen, Y.; and Zhou, B. 2020 · 2012
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Big Data: Issues, Challenges, Tools and Good Practices
Katal, A.; Wazid, M.; and Goudar, R. H. 2013 · 2013
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Generative adversarial nets
Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2014 · 2014
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How transferable are features in deep neural networks?
Yosinski, J.; Clune, J.; Bengio, Y.; and Lipson, H. 2014 · 2014
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Certifying and removing disparate impact
Feldman, M.; Friedler, S. A.; Moeller, J.; Scheidegger, C.; and Venkatasubramanian, S. 2015 · 2015
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Deep Learning Face Attributes in the Wild
Liu, Z.; Luo, P.; Wang, X.; and Tang, X. 2015 · 2015
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Equality of opportunity in supervised learning
Hardt, M.; Price, E.; and Srebro, N. 2016 · 2016
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Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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TARGET – Taking a Reflexive Approach to Gender Equality for Institutional Transformation
Chizzola, V.; Micheli, B.; and Vingelli. 2017 · 2017
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GENERATIVE MULTI-ADVERSARIAL NETWORKS
Durugkar, I.; Gemp, I.; and Mahadevan, S. 2017 · 2017
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Aircraft fuselage defect detection using deep neural networks
Malekzadeh, T.; Abdollahzadeh, M.; Nejati, H.; and Cheung, N.-M. 2017 · 2017
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Dual Discriminator Generative Adversarial Nets
Nguyen, T.; Le, T.; Vu, H.; and Phung, D. 2017 · 2017
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Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
Schlegl, T.; Seeböck, P.; Waldstein, S. M.; Schmidt-Erfurth, U.; and Langs, G. 2017 · 2017
Earlier work this paper cites.
Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Zhang, H.; Xu, T.; Li, H.; Zhang, S.; Wang, X.; Huang, X.; and Metaxas, D. N. 2017 · 2017
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Age progression/regression by conditional adversarial autoencoder
Zhang, Z.; Song, Y.; and Qi, H. 2017 · 2017
Cited alongside, same era.
Fair Generation Through Prior Modification
Frankel, E.; and Vendrow, E. 2020 · 2018
Cited alongside, same era.
GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification
Frid-Adar, M.; Diamant, I.; Klang, E.; Amitai, M.; Goldberger, J.; and Greenspan, H. 2018 · 2018
Cited alongside, same era.
Multi-Agent Diverse Generative Adversarial Networks
Ghosh, A.; Kulharia, V.; Namboodiri, V.; Torr, P. H. S.; and Dokania, P. K. 2018 · 2018
Cited alongside, same era.
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Heusel, M.; Ramsauer, H.; Unterthiner, T.; Nessler, B.; and Hochreiter, S. 2018 · 2018
Cited alongside, same era.
Few-Shot Learning via Learning the Representation, Provably
Du, S. S.; Hu, W.; Kakade, S. M.; Lee, J. D.; and Lei, Q. 2020 · 2020
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FairFaceGAN: Fairness-aware Facial Image-to-Image Translation
Hwang, S. 2020 · 2020
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Suspect Face Generation
Jalan, H. J.; Maurya, G.; Corda, C.; Dsouza, S.; and Panchal, D. 2020 · 2020
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Few-Shot Image Generation with Elastic Weight Consolidation
Li, Y.; Zhang, R.; Lu, J. C.; and Shechtman, E. 2020 · 2020
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Deep artifact-free residual network for single-image super-resolution
Nasrollahi, H.; Farajzadeh, K.; Hosseini, V.; Zarezadeh, E.; and Abdollahzadeh, M. 2020 · 2020
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On Leveraging Pretrained GANs for Generation with Limited Data
Zhao, M.; Cong, Y.; and Carin, L. 2020 · 2020
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Progressive Growing of GANs for Improved Quality, Stability, and Variation
Karras, T.; Aila, T.; Laine, S.; and Lehtinen, J. 2018 · 2018
Cited alongside, same era.
DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection
Lim, S. K.; Loo, Y.; Tran, N.-T.; Cheung, N.-M.; Roig, G.; and Elovici, Y. 2018 · 2018
Cited alongside, same era.
Transferring GANs: Generating Images from Limited Data
Wang, Y.; Wu, C.; Herranz, L.; van de Weijer, J.; Gonzalez-Garcia, A.; and Raducanu, B. 2018b · 2018
Cited alongside, same era.
Fairgan: Fairness-aware generative adversarial networks
Xu, D.; Yuan, S.; Zhang, L.; and Wu, X. 2018 · 2018
Cited alongside, same era.
Video captioning by adversarial LSTM
Yang, Y.; Zhou, J.; Ai, J.; Bin, Y.; Hanjalic, A.; Shen, H. T.; and Ji, Y. 2018 · 2018
Cited alongside, same era.
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Brock, A.; Donahue, J.; and Simonyan, K. 2019 · 2019
Cited alongside, same era.
On-device image classification with proxyless neural architecture search and quantization-aware fine-tuning
Cai, H.; Wang, T.; Wu, Z.; Wang, K.; Lin, J.; and Han, S. 2019 · 2019
Cited alongside, same era.
Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning
Abdollahzadeh, M.; Malekzadeh, T.; and Cheung, N.-M. M. 2021 · 2021
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Collecting data on textiles from the internet using web crawling and web scraping tools
Muehlethaler, C.; and Albert, R. 2021 · 2021
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Few-Shot Image Generation via Cross-domain Correspondence
Ojha, U.; Li, Y.; Lu, J.; Efros, A. A.; Jae Lee, Y.; Shechtman, E.; and Zhang, R. 2021 · 2021
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On Data Augmentation for GAN Training
Tran, N.-T.; Tran, V.-H.; Nguyen, N.-B.; Nguyen, T.-K.; and Cheung, N.-M. 2021 · 2021
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A Fair Generative Model Using Total Variation Distance
Um, S.; and Suh, C. 2021 · 2021
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Multi-Objective Training of Generative Adversarial Networks with Multiple Discriminators
Albuquerque, I.; Monteiro, J.; Doan, T.; Considine, B.; Falk, T.; and Mitliagkas, I. 2022 · 2022
Closest in time.
MGAN: Training Generative Adversarial Nets with Multiple Generators
Hoang, Q.; Nguyen, T. D.; Le, T.; and Phung, D. 2022 · 2022
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MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining
Humayun, A. I.; Balestriero, R.; and Baraniuk, R. 2022 · 2022
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Transferability in Deep Learning: A Survey
Jiang, J.; Shu, Y.; Wang, J.; and Long, M. 2022 · 2022
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Fine-Tuning Can Distort Pretrained Features and Underperform Out-of-Distribution
Kumar, A.; Raghunathan, A.; Jones, R.; Ma, T.; and Liang, P. 2022 · 2022
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Ensembling Off-the-Shelf Models for GAN Training
Kumari, N.; Zhang, R.; Shechtman, E.; and Zhu, J.-Y. 2022 · 2022
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A survey on datasets for fairness-aware machine learning
Le Quy, T.; Roy, A.; Iosifidis, V.; Zhang, W.; and Ntoutsi, E. 2022 · 2022
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Few-shot Image Generation via Adaptation-Aware Kernel Modulation
Zhao, Y.; Chandrasegaran, K.; Abdollahzadeh, M.; and man Cheung, N. 2022 · 2022
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