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Scheduling

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/svtdanny/diagonal-batching

공식 코드

Diagonal Batching Unlocks Parallelism in Recurrent Memory Transformers for Long Contexts

https://github.com/sydney-machine-learning/MEHH_RCPSP

공식 코드

MAP-Elites based Hyper-Heuristic for the Resource Constrained Project Scheduling Problem

https://github.com/symbioticlab/venn

공식 코드

Venn: Resource Management for Collaborative Learning Jobs

https://github.com/sysal-bruce-publication/Uncertain-Dynamic-OP

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Adaptive Probabilistic Planning for the Uncertain and Dynamic Orienteering Problem

https://github.com/taskflow/taskflow

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Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System

https://github.com/thaihungle/EPGT

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Episodic Policy Gradient Training

https://github.com/tharaka-perera/flex-net

공식 코드

Flex-Net: A Graph Neural Network Approach to Resource Management in Flexible Duplex Networks

https://github.com/thinklab-sjtu/ppo-bihyb

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A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs

https://github.com/thinklab-sjtu/predictiveco-benchmark

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Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime

https://github.com/thomasmong/llm-power-scheduling

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Large Language Models for Power Scheduling: A User-Centric Approach

https://github.com/tiannuo-yang/searchagent-x

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Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agents

https://github.com/tlavastida/predictionportfolios

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Algorithms with Prediction Portfolios

https://github.com/tmdt-buw/schlably

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schlably: A Python Framework for Deep Reinforcement Learning Based Scheduling Experiments

https://github.com/tongyi-zhiwen/writing-rl

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Writing-RL: Advancing Long-form Writing via Adaptive Curriculum Reinforcement Learning

https://github.com/treeai-lab/awesome-kv-cache-management

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A Survey on Large Language Model Acceleration based on KV Cache Management

https://github.com/tsinghua-fib-lab/LLM-for-User-Intent

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A Population-to-individual Tuning Framework for Adapting Pretrained LM to On-device User Intent Prediction

https://github.com/tsinghua-fib-lab/sand

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Learning to Simulate Daily Activities via Modeling Dynamic Human Needs

https://github.com/tsunghan-wu/d2ada

공식 코드

D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation

https://github.com/tum-ei-eda/moiopt

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Fused Depthwise Tiling for Memory Optimization in TinyML Deep Neural Network Inference

https://github.com/tumbais/structured-rl

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Structured Reinforcement Learning for Combinatorial Decision-Making

https://github.com/ubiquitouslearning/nnv12

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Boosting DNN Cold Inference on Edge Devices

https://github.com/ujohn33/citylearn_scenarios

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Balancing Forecast Accuracy and Switching Costs in Online Optimization of Energy Management Systems

https://github.com/um-dsp/morphence

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Morphence-2.0: Evasion-Resilient Moving Target Defense Powered by Out-of-Distribution Detection

https://github.com/unites-lab/q-newton

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Q-Newton: Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent

https://github.com/ut-amrl/graph_navigation

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Decentralized Social Navigation with Non-Cooperative Robots via Bi-Level Optimization

https://github.com/vfleaking/rnnprop

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Learning Gradient Descent: Better Generalization and Longer Horizons

https://github.com/victormvy/sigma-convkernels

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A hybrid feature learning approach based on convolutional kernels for ATM fault prediction using event-log data

https://github.com/vita-group/read-me

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Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design

https://github.com/vithursant/SPL-ADVisE

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Self-Paced Learning with Adaptive Deep Visual Embeddings

https://github.com/vnatesh/rosko

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Rosko: Row Skipping Outer Products for Sparse Matrix Multiplication Kernels

https://github.com/waynemao/robomatrix

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RoboMatrix: A Skill-centric Hierarchical Framework for Scalable Robot Task Planning and Execution in Open-World

https://github.com/weifantt/depts

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DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting

https://github.com/wenyueh/latency_optimization_with_priority_constraints

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Semantic Scheduling for LLM Inference

https://github.com/wildsky95/ZT-PFR

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Proactive and AoI-aware Failure Recovery for Stateful NFV-enabled Zero-Touch 6G Networks: Model-Free DRL Approach

https://github.com/willtl/online-printing-shop

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Metaheuristics for the Online Printing Shop Scheduling Problem

https://github.com/willwang1113/multiresolutionforecasting

공식 코드

Seamless and multi-resolution energy forecasting

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