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Scheduling
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Autonomous Resource Management in Microservice Systems via Reinforcement Learning
Fremer: Lightweight and Effective Frequency Transformer for Workload Forecasting in Cloud Services
Leveraging Asynchronous Cross-border Market Data for Improved Day-Ahead Electricity Price Forecasting in European Markets
Transient-Stability-Aware Frequency Provision in IBR-Rich Grids via Information Gap Decision Theory and Deep Learning
FormulaOne: Measuring the Depth of Algorithmic Reasoning Beyond Competitive Programming
Optimal Sensor Scheduling and Selection for Continuous-Discrete Kalman Filtering with Auxiliary Dynamics
SystolicAttention: Fusing FlashAttention within a Single Systolic Array
Elk: Exploring the Efficiency of Inter-core Connected AI Chips with Deep Learning Compiler Techniques
BitParticle: Partializing Sparse Dual-Factors to Build Quasi-Synchronizing MAC Arrays for Energy-efficient DNNs
An Adaptive Volatility-based Learning Rate Scheduler
Hierarchical Task Offloading for UAV-Assisted Vehicular Edge Computing via Deep Reinforcement Learning
OpenAgentSafety: A Comprehensive Framework for Evaluating Real-World AI Agent Safety
ANN-Based Grid Impedance Estimation for Adaptive Gain Scheduling in VSG Under Dynamic Grid Conditions
Co-Design of Sensing, Communications, and Control for Low-Altitude Wireless Networks
Improving Diffusion-Based Image Editing Faithfulness via Guidance and Scheduling
Joint Scheduling of DER under Demand Charges: Structure and Approximation
Predictive Maintenance Optimization for Smart Vending Machines Using IoT and Machine Learning
MAGPIE: A dataset for Multi-AGent contextual PrIvacy Evaluation
MILAAP: Mobile Link Allocation via Attention-based Prediction
Finite-Time Information-Theoretic Bounds in Queueing Control
Confucius3-Math: A Lightweight High-Performance Reasoning LLM for Chinese K-12 Mathematics Learning
Plan for Speed -- Dilated Scheduling for Masked Diffusion Language Models
ConsumerBench: Benchmarking Generative AI Applications on End-User Devices
Research on Model Parallelism and Data Parallelism Optimization Methods in Large Language Model-Based Recommendation Systems
RapFlow-TTS: Rapid and High-Fidelity Text-to-Speech with Improved Consistency Flow Matching
All is Not Lost: LLM Recovery without Checkpoints
A Simplified Analysis of SGD for Linear Regression with Weight Averaging
Considering the multi-time scale rolling optimization scheduling method of micro-energy network connected to electric vehicles
ASAP-FE: Energy-Efficient Feature Extraction Enabling Multi-Channel Keyword Spotting on Edge Processors
Efficient Serving of LLM Applications with Probabilistic Demand Modeling
CNN-Enabled Scheduling for Probabilistic Real-Time Guarantees in Industrial URLLC
GCN-Driven Reinforcement Learning for Probabilistic Real-Time Guarantees in Industrial URLLC
AlphaEvolve: A coding agent for scientific and algorithmic discovery
Vine Copulas as Differentiable Computational Graphs
A Production Scheduling Framework for Reinforcement Learning Under Real-World Constraints
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.