task scheduling

Cook and Clean Together: Teaching Embodied Agents for Parallel Task Execution AAAI 2026 ProActor: Timing-Aware Reinforcement Learning for Proactive Task Scheduling Agents ACL 2026 SpiderFlow: Efficient Topology-Aware Scheduling for LLM Training Across Decentralized GPU Clusters ACL 2026 Unleash All Cores: Asymmetry-Aware Scalable DNN Inference on Mobile CPUs OSDI 2026 μShell: A Microkernel-based FPGA Shell Architecture OSDI 2026 COLA: Collaborative Multi-Agent Framework with Dynamic Task Scheduling for GUI Automation EMNLP 2025 Preventing Network Bottlenecks: Accelerating Datacenter Services with Hotspot-Aware Placement for Compute and Storage NSDI 2025 Robotouille: An Asynchronous Planning Benchmark for LLM Agents ICLR 2025 Hard Tasks First: Multi-Task Reinforcement Learning Through Task Scheduling ICML 2024 Horus: Granular In-Network Task Scheduler for Cloud Datacenters NSDI 2024 FastGR: Global Routing on CPU-GPU with Heterogeneous Task Graph Scheduler (Extended Abstract) IJCAI 2023 Meta-Learning with Neural Bandit Scheduler NeurIPS 2023 Auxiliary Learning with Joint Task and Data Scheduling ICML 2022 Efficient Scheduling Policies for Microsecond-Scale Tasks NSDI 2022 Q-Learning Scheduler for Multi Task Learning Through the use of Histogram of Task Uncertainty ACL 2022 Caerus: NIMBLE Task Scheduling for Serverless Analytics NSDI 2021 Fast Learning for Renewal Optimization in Online Task Scheduling JMLR 2021 Temporally Correlated Task Scheduling for Sequence Learning ICML 2021 Automatic Curriculum Learning For Deep RL: A Short Survey IJCAI 2020 Sol: Fast Distributed Computation Over Slow Networks NSDI 2020 Which Tasks Should Be Learned Together in Multi-task Learning? ICML 2020 Hydra: a federated resource manager for data-center scale analytics NSDI 2019 CLARINET: WAN-Aware Optimization for Analytics Queries OSDI 2016