A review on bilevel optimization: From classical to evolutionary approaches and applications
Bilevel optimization is defined as a mathematical program, where an optimization problem
contains another optimization problem as a constraint. These problems have received …
contains another optimization problem as a constraint. These problems have received …
[HTML][HTML] A survey on mixed-integer programming techniques in bilevel optimization
Bilevel optimization is a field of mathematical programming in which some variables are
constrained to be the solution of another optimization problem. As a consequence, bilevel …
constrained to be the solution of another optimization problem. As a consequence, bilevel …
A fully first-order method for stochastic bilevel optimization
We consider stochastic unconstrained bilevel optimization problems when only the first-
order gradient oracles are available. While numerous optimization methods have been …
order gradient oracles are available. While numerous optimization methods have been …
A two-timescale stochastic algorithm framework for bilevel optimization: Complexity analysis and application to actor-critic
This paper analyzes a two-timescale stochastic algorithm framework for bilevel optimization.
Bilevel optimization is a class of problems which exhibits a two-level structure, and its goal is …
Bilevel optimization is a class of problems which exhibits a two-level structure, and its goal is …
Data distillation: A survey
The popularity of deep learning has led to the curation of a vast number of massive and
multifarious datasets. Despite having close-to-human performance on individual tasks …
multifarious datasets. Despite having close-to-human performance on individual tasks …
Investigating bi-level optimization for learning and vision from a unified perspective: A survey and beyond
Bi-Level Optimization (BLO) is originated from the area of economic game theory and then
introduced into the optimization community. BLO is able to handle problems with a …
introduced into the optimization community. BLO is able to handle problems with a …
On penalty-based bilevel gradient descent method
Bilevel optimization enjoys a wide range of applications in hyper-parameter optimization,
meta-learning and reinforcement learning. However, bilevel problems are difficult to solve …
meta-learning and reinforcement learning. However, bilevel problems are difficult to solve …
Advancing model pruning via bi-level optimization
The deployment constraints in practical applications necessitate the pruning of large-scale
deep learning models, ie, promoting their weight sparsity. As illustrated by the Lottery Ticket …
deep learning models, ie, promoting their weight sparsity. As illustrated by the Lottery Ticket …
Revisiting and advancing fast adversarial training through the lens of bi-level optimization
Adversarial training (AT) is a widely recognized defense mechanism to gain the robustness
of deep neural networks against adversarial attacks. It is built on min-max optimization …
of deep neural networks against adversarial attacks. It is built on min-max optimization …
A near-optimal algorithm for stochastic bilevel optimization via double-momentum
This paper proposes a new algorithm--the\underline {S} ingle-timescale Do\underline {u} ble-
momentum\underline {St} ochastic\underline {A} pprox\underline {i} matio\underline …
momentum\underline {St} ochastic\underline {A} pprox\underline {i} matio\underline …