Research map / Reinforcement learning / Policy gradient and actor-critic
Learning to Optimize
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the learned autonomous optimizer instead of gradient descent | Logistic regression · Logistic regression test objectives | convergence speed | Helped |
| Use the learned autonomous optimizer instead of L-BFGS | Logistic regression · Logistic regression test objectives | final objective value | Mixed |
| Use the learned autonomous optimizer instead of gradient descent, conjugate gradient, or L-BFGS | Robust linear regression · Robust linear regression test objectives | convergence speed | Helped |
| Use the learned autonomous optimizer instead of momentum | Robust linear regression · Robust linear regression test objectives | convergence speed | Mixed |
| Use the learned autonomous optimizer instead of hand-engineered optimizers | Two-layer neural net classifier · Neural net classifier test objectives | final objective value | Helped |
| Use the learned autonomous optimizer instead of hand-engineered optimizers | Two-layer neural net classifier · Neural net classifier test objectives | convergence speed | Helped |
Closest papers by meaning
- Teacher-Aware Evolution of Heuristic Programs from Learned Optimization Policies (NeurIPS 2026 · similarity 0.88)
- Can Learned Optimization Make Reinforcement Learning Less Difficult? (NeurIPS 2024 · similarity 0.87)
- DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization (NeurIPS 2025 · similarity 0.87)
- Preference Optimization for Combinatorial Optimization Problems (ICML 2025 · similarity 0.86)
- Discovering Temporally-Aware Reinforcement Learning Algorithms (ICLR 2024 · similarity 0.85)
- Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces (NeurIPS 2026 · similarity 0.85)
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