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Bi-level optimization model is able to capture a wide range of complex learning tasks with practical interest.
The polynomial hierarchy and a simple model for competitive analysis
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On the numerical solution of a class of stackelberg problems
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Optimality conditions for bilevel programming problems
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Imagenet: A large-scale hierarchical image database
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Sequential model-based optimization for general algorithm configuration
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Random search for hyper-parameter optimization
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Perturbation analysis of optimization problems
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Human-level concept learning through probabilistic program induction
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Hyperparameter optimization with approximate gradient
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Connecting generative adversarial networks and actor-critic methods
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Matching networks for one shot learning
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Forward and reverse gradient-based hyperparameter optimization
Franceschi, L., Donini, M., Frasconi, P., and Pontil, M · 2017
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Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms
Xiao, H., Rasul, K., and Vollgraf, R · 2017
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Bilevel optimization: theory, algorithms and applications
Dempe, S · 2018
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Bilevel programming for hyperparameter optimization and meta-learning
Franceschi, L., Frasconi, P., Salzo, S., Grazzi, R., and Pontil, M · 2018
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Self-tuning networks: Bilevel optimization of hyperparameters using structured best-response functions
Meta-learning with implicit gradients
Rajeswaran, A., Finn, C., Kakade, S. M., and Levine, S · 2019
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Truncated back-propagation for bilevel optimization
Shaban, A., Cheng, C., Hatch, N., and Boots, B · 2019
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Provably global convergence of actor-critic: A case for linear quadratic regulator with ergodic cost
Yang, Z., Chen, Y., Hong, M., and Wang, Z · 2019
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Adversarial attacks on graph neural networks via meta learning
Zügner, D. and Günnemann, S · 2019
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A regularized smoothing method for fully parameterized convex problems with applications to convex and nonconvex two-stage stochastic programming
Borges, P., Sagastizábal, C., and Solodov, M · 2020
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Mackay, M., Vicol, P., Lorraine, J., Duvenaud, D., and Grosse, R · 2018
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Okuno, T., Takeda, A., and Kawana, A · 2018
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Progressive differentiable architecture search: Bridging the depth gap between search and evaluation
Chen, X., Xie, L., Wu, J., and Tian, Q · 2019
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Generalized inner loop meta-learning
Grefenstette, E., Amos, B., Yarats, D., Htut, P. M., Molchanov, A., Meier, F., Kiela, D., Cho, K., and Chintala, S · 2019
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DARTS: differentiable architecture search
Liu, H., Simonyan, K., and Yang, Y
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On the convergence of learning-based iterative methods for nonconvex inverse problems
Liu, R., Cheng, S., He, Y., Fan, X., Lin, Z., and Luo, Z
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On the iteration complexity of hypergradient computation
Grazzi, R., Franceschi, L., Pontil, M., and Salzo, S · 2020
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Bilevel optimization: Nonasymptotic analysis and faster algorithms
Ji, K., Yang, J., and Liang, Y · 2020
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Optimizing millions of hyperparameters by implicit differentiation
Lorraine, J., Vicol, P., and Duvenaud, D · 2020
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Lower bounds and accelerated algorithms for bilevel optimization
Ji, K. and Liang, Y · 2021
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Liu, R., Gao, J., Zhang, J., Meng, D., and Lin, Z · 2021
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