Cover Image

Machine Learning for Energy-Performance-aware Scheduling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hu, Zheyuan, Shi, Yifei
Format:	Preprint
Published:	2026
Subjects:	Hardware Architecture Artificial Intelligence Machine Learning C.4; I.2.6; I.2.8
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

EM-Aware Physical Synthesis: Neural Inductor Modeling and Intelligent Placement & Routing for RF Circuits
by: Huang, Yilun, et al.
Published: (2026)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding
by: Li, Yifei, et al.
Published: (2025)

Learning, Fast and Slow: Towards LLMs That Adapt Continually
by: Tiwari, Rishabh, et al.
Published: (2026)

What Do World Models Learn in RL? Probing Latent Representations in Learned Environment Simulators
by: Zhang, Xinyu
Published: (2026)

Working Paper: Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
by: Riscos, Pablo de los, et al.
Published: (2024)

CORE: Constraint-Aware One-Step Reinforcement Learning for Simulation-Guided Neural Network Accelerator Design
by: Xiao, Yifeng, et al.
Published: (2025)

Safe Reinforcement Learning with Preference-based Constraint Inference
by: Li, Chenglin, et al.
Published: (2026)

Adaptable Hindsight Experience Replay for Search-Based Learning
by: Vazaios, Alexandros, et al.
Published: (2025)

CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
by: Sauter, Andreas W. M., et al.
Published: (2024)

Differentiable Symbolic Planning: A Neural Architecture for Constraint Reasoning with Learned Feasibility
by: Oruganti, Venkatakrishna Reddy
Published: (2026)

GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control
by: Hiremath, Prakul Sunil
Published: (2026)

Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems
by: Nuzhin, Egor E., et al.
Published: (2024)

From Next Token Prediction to (STRIPS) World Models
by: Núñez-Molina, Carlos, et al.
Published: (2025)

Regret-Aware Policy Optimization: Environment-Level Memory for Replay Suppression under Delayed Harm
by: Hiremath, Prakul Sunil
Published: (2026)

On the Generalization Gap in LLM Planning: Tests and Verifier-Reward RL
by: Belcamino, Valerio, et al.
Published: (2026)

Not All Transitions Matter: Evidence from PPO
by: Basnet, Ajhesh
Published: (2026)

AGWM: Affordance-Grounded World Models for Environments with Compositional Prerequisites
by: Zhang, Qinshi, et al.
Published: (2026)

Embedded Safety-Aligned Intelligence via Differentiable Internal Alignment Embeddings
by: Rathva, Harsh, et al.
Published: (2025)

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
by: Zawalski, Michał, et al.
Published: (2022)

Incentives for Responsiveness, Instrumental Control and Impact
by: Carey, Ryan, et al.
Published: (2020)

Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
by: Kang, Jiyeon, et al.
Published: (2025)

When Outcome Looks Right But Discipline Fails: Trace-Based Evaluation Under Hidden Competitor State
by: Zhu, Peiying, et al.
Published: (2026)

The Final-Stage Bottleneck: A Systematic Dissection of the R-Learner for Network Causal Inference
by: Sairam, S, et al.
Published: (2025)

On the Limits of Learned Importance Scoring for KV Cache Compression
by: Steele, Brady
Published: (2026)

Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
by: Silue, Bram, et al.
Published: (2025)

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
by: Vincze, Mátyás, et al.
Published: (2024)

HERO: Hint-Based Efficient and Reliable Query Optimizer
by: Zinchenko, Sergey, et al.
Published: (2024)

Learning to Select Goals in Automated Planning with Deep-Q Learning
by: Núñez-Molina, Carlos, et al.
Published: (2024)

LakeMLB: Data Lake Machine Learning Benchmark
by: Pan, Feiyu, et al.
Published: (2026)

Resolving Action Bottleneck: Agentic Reinforcement Learning Informed by Token-Level Energy
by: He, Langzhou, et al.
Published: (2026)

SCULPT: Constraint-Guided Pruned MCTS that Carves Efficient Paths for Mathematical Reasoning
by: Fang, Qitong, et al.
Published: (2026)

Scaling Trends for Multi-Hop Contextual Reasoning in Mid-Scale Language Models
by: Steele, Brady, et al.
Published: (2026)

The ARC of Progress towards AGI: A Living Survey of Abstraction and Reasoning
by: Vahdati, Sahar, et al.
Published: (2026)

Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
by: Aichmüller, Michael, et al.
Published: (2024)

NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
by: Núñez-Molina, Carlos, et al.
Published: (2023)

The Shortcomings of Force-from-Motion in Robot Learning
by: Aljalbout, Elie, et al.
Published: (2024)

MOCHA: Multi-Objective Chebyshev Annealing for Agent Skill Optimization
by: Tanjim, Md Mehrab, et al.
Published: (2026)

Social Interpretable Reinforcement Learning
by: Custode, Leonardo Lucio, et al.
Published: (2024)

A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
by: Wang, Yuxuan, et al.
Published: (2025)