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Scheduling

Project or Job Scheduling

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Showing 2701–2750 of 3104 papers

TitleStatusHype
Scheduling Policy for Value-of-Information (VoI) in Trajectory Estimation for Digital Twins—0
Scheduling Power-Intensive Operations of Battery Energy Storage Systems and Application to Hybrid Hydropower Plants—0
Scheduling Quantum Annealing for Active User Detection in a NOMA Network—0
Scheduling Real-time Deep Learning Services as Imprecise Computations—0
Scheduling Techniques for Liver Segmentation: ReduceLRonPlateau Vs OneCycleLR—0
Scheduling the Learning Rate Via Hypergradients: New Insights and a New Algorithm—0
Scheduling the NASA Deep Space Network with Deep Reinforcement Learning—0
Scheduling to Learn In An Unsupervised Online Streaming Model—0
Scheduling with Predictions—0
Scheduling with Speed Predictions—0
Scheduling with Uncertain Holding Costs and its Application to Content Moderation—0
School bus routing by maximizing trip compatibility—0
ScopeIt: Scoping Task Relevant Sentences in Documents—0
SCORPIO: Serving the Right Requests at the Right Time for Heterogeneous SLOs in LLM Inference—0
SDRL: Interpretable and Data-efficient Deep Reinforcement Learning Leveraging Symbolic Planning—0
DREAM: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads—0
Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation—0
Secrecy Performance of a Keyhole-based Multi-user System with Multiple Eavesdroppers—0
SelectFormer: Private and Practical Data Selection for Transformers—0
Securing FC-RIS and UAV Empowered Multiuser Communications Against a Randomly Flying Eavesdropper—0
Security Defense of Large Scale Networks Under False Data Injection Attacks: An Attack Detection Scheduling Approach—0
Seesaw: High-throughput LLM Inference via Model Re-sharding—0
See the Near Future: A Short-Term Predictive Methodology to Traffic Load in ITS—0
Self-Configuring nnU-Nets Detect Clouds in Satellite Images—0
Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning—0
Self-encoding Barnacle Mating Optimizer Algorithm for Manpower Scheduling in Flow Shop—0
Self-Evaluation for Job-Shop Scheduling—0
Self-Nomination: Deep Learning for Decentralized CSI Feedback Reduction in MU-MIMO Systems—0
Semantic-Aware Remote Estimation of Multiple Markov Sources Under Constraints—0
Semantic-aware Transmission Scheduling: a Monotonicity-driven Deep Reinforcement Learning Approach—0
Semantic Text Transmission via Prediction with Small Language Models: Cost-Similarity Trade-off—0
Semi-Blind Post-Equalizer SINR Estimation and Dual CSI Feedback for Radar-Cellular Coexistence—0
Semi-Clairvoyant Scheduling of Speculative Decoding Requests to Minimize LLM Inference Latency—0
semi-PD: Towards Efficient LLM Serving via Phase-Wise Disaggregated Computation and Unified Storage—0
Semi-supervised Breast Lesion Detection in Ultrasound Video Based on Temporal Coherence—0
Semi-Synchronous Personalized Federated Learning over Mobile Edge Networks—0
Send Pilot or Data? Leveraging Age of Channel State Information for Throughput Maximization—0
Sensing-Aided Peer-to-Peer Millimeter-Wave Communication—0
Sensing Capacity for Integrated Sensing and Communication Systems in Low-Altitude Economy—0
Sensor Scheduling Design for Complex Networks under a Distributed State Estimation Framework—0
Sensor Scheduling for Linear Systems: A Covariance Tracking Approach—0
Sensor Scheduling in Intrusion Detection Games with Uncertain Payoffs—0
Sentinel: Scheduling Live Streams with Proactive Anomaly Detection in Crowdsourced Cloud-Edge Platforms—0
Separated Contrastive Learning for Matching in Cross-domain Recommendation with Curriculum Scheduling—0
Sequence-to-sequence models for workload interference—0
Constrained Restless Bandits for Dynamic Scheduling in Cyber-Physical Systems—0
Sequential learning and control: Targeted exploration for robust performance—0
Service Scheduling for Random Requests with Fixed Waiting Costs—0
Service Scheduling for Random Requests with Quadratic Waiting Costs—0
Serving DNN Models with Multi-Instance GPUs: A Case of the Reconfigurable Machine Scheduling Problem—0
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