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In recent years, a variety of gradient-based first-order methods have been developed to solve bi-level optimization problems for learning applications.
The polynomial hierarchy and a simple model for competitive analysis
Jeroslow, R. G · 1985
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Gradient-based learning applied to document recognition
LeCun, Y., Bottou, L., Bengio, Y., Haffner, P., et al · 1998
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Convergence of a block coordinate descent method for nondifferentiable minimization
Tseng, P · 2001
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Classification model selection via bilevel programming
Kunapuli, G., Bennett, K. P., Hu, J., and Pang, J.-S · 2008
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A fast iterative shrinkage-thresholding algorithm for linear inverse problems
Beck, A. and Teboulle, M · 2009
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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Variational analysis
Rockafellar, R. T. and Wets, R. J.-B · 2009
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Bilevel programming algorithms for machine learning model selection
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Generic methods for optimization-based modeling
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Perturbation analysis of optimization problems
Bonnans, J. F. and Shapiro, A · 2013
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A bilevel optimization approach for parameter learning in variational models
Kunisch, K. and Pock, T · 2013
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Human-level concept learning through probabilistic program induction
Lake, B. M., Salakhutdinov, R., and Tenenbaum, J. B · 2015
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Gradient-based hyperparameter optimization through reversible learning
Maclaurin, D., Duvenaud, D., and Adams, R · 2015
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Connecting generative adversarial networks and actor-critic methods
Pfau, D. and Vinyals, O · 2016
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Matching networks for one shot learning
Vinyals, O., Blundell, C., Lillicrap, T., Wierstra, D., et al · 2016
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Proximal deep structured models
Wang, S., Fidler, S., and Urtasun, R · 2016
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Automatic differentiation in machine learning: a survey
Baydin, A. G., Pearlmutter, B. A., Radul, A. A., and Siskind, J. M · 2017
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First-order methods in optimization
Beck, A · 2017
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Deep bilevel learning
Jenni, S. and Favaro, P · 2018
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Meta-sgd: Learning to learn quickly for few-shot learning
Li, Z., Zhou, F., Chen, F., and Li, H · 2018
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Stochastic hyperparameter optimization through hypernetworks
Lorraine, J. and Duvenaud, D · 2018
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On first-order meta-learning algorithms
Nichol, A., Achiam, J., and Schulman, J · 2018
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Hyperparameter learning via bilevel nonsmooth optimization
Okuno, T., Takeda, A., and Kawana, A · 2018
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Finn, C., Abbeel, P., and Levine, S · 2017
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Forward and reverse gradient-based hyperparameter optimization
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Few-shot image recognition by predicting parameters from activations
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Meta-learning with implicit gradients
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Truncated back-propagation for bilevel optimization
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Provably global convergence of actor-critic: A case for linear quadratic regulator with ergodic cost
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Adversarial attacks on graph neural networks via meta learning
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