Personalized Execution Time Optimization for Billion-Scale Scheduled Jobs

arXiv:2203.06158 · cs.LG, cs.DC · Submitted 2022-03-11 · Read on arXiv

cs.LG, cs.DC

Submitted: 2022-03-11

Updated: 2026-09-09

Comments: conference

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Ensemble Learning — 5× in this paper · explained in 2 episodes
• Reinforcement Learning — 4× in this paper · explained in 4 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• Seq2Slate: Re-ranking and Slate Optimization with RNNs
• Feature-Weighted Linear Stacking

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks