Imagen de Portada

Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Naser-Moghadasi, Mahdi
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Databases I.2.6; H.2.4
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

Transformers Meet Relational Databases
por: Peleška, Jakub, et al.
Publicado: (2024)

Bi-View Embedding Fusion: A Hybrid Learning Approach for Knowledge Graph's Nodes Classification Addressing Problems with Limited Data
por: Napoli, Rosario, et al.
Publicado: (2025)

Automated Database Indexing using Model-free Reinforcement Learning
por: Licks, Gabriel Paludo, et al.
Publicado: (2020)

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

Transformer Scalability Crisis: The First Comprehensive Empirical Analysis of Performance Walls in Modern Language Models
por: Moghadasi, Mahdi Naser, et al.
Publicado: (2026)

Ground-Compose-Reinforce: Grounding Language in Agentic Behaviours using Limited Data
por: Li, Andrew C., et al.
Publicado: (2025)

Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms
por: Avery, Katherine, et al.
Publicado: (2025)

Sensorformer: Cross-patch attention with global-patch compression is effective for high-dimensional multivariate time series forecasting
por: Qin, Liyang, et al.
Publicado: (2025)

Neural Activation Patterns Across Language Model Architectures: A Comprehensive Analysis of Cognitive Task Performance
por: Naser-Moghadasi, Mahdi, et al.
Publicado: (2026)

Samyama: A Unified Graph-Vector Database with In-Database Optimization, Agentic Enrichment, and Hardware Acceleration
por: Mandarapu, Madhulatha, et al.
Publicado: (2026)

A Grammar of Machine Learning Workflows: Rejecting Data Leakage at Call Time
por: Roth, Simon
Publicado: (2026)

LiveVectorLake: A Real-Time Versioned Knowledge Base Architecture for Streaming Vector Updates and Temporal Retrieval
por: Prajapati, Tarun
Publicado: (2025)

HEHRGNN: A Unified Embedding Model for Knowledge Graphs with Hyperedges and Hyper-Relational Edges
por: Rajagopalamenon, Rajesh, et al.
Publicado: (2026)

Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models
por: Nicolau, Marcio, et al.
Publicado: (2020)

Unlocking Advanced Graph Machine Learning Insights through Knowledge Completion on Neo4j Graph Database
por: Napoli, Rosario, et al.
Publicado: (2025)

Memory-Efficient Partitioned DNN Inference on Resource-Constrained Android Crowds
por: Manamperi, Lakshani, et al.
Publicado: (2026)

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

Study Design and Demystification of Physics Informed Neural Networks for Power Flow Simulation
por: Leyli-abadi, Milad, et al.
Publicado: (2025)

Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines"
por: Grafberger, Stefan, et al.
Publicado: (2024)

Prior-Aligned Data Cleaning for Tabular Foundation Models
por: Berti-Equille, Laure
Publicado: (2026)

ComplianceNLP: Knowledge-Graph-Augmented RAG for Multi-Framework Regulatory Gap Detection
por: Guo, Dongxin, et al.
Publicado: (2026)

Graph Spring Neural ODEs for Link Sign Prediction
por: Rehmann, Andrin, et al.
Publicado: (2024)

Generative and Contrastive Graph Representation Learning
por: Chen, Jiali, et al.
Publicado: (2025)

VN Network: Embedding Newly Emerging Entities with Virtual Neighbors
por: He, Yongquan, et al.
Publicado: (2024)

The CTU Prague Relational Learning Repository
por: Motl, Jan, et al.
Publicado: (2015)

Federated Continual Recommendation
por: Lim, Jaehyung, et al.
Publicado: (2025)

rmlnomogram: An R package to construct an explainable nomogram for any machine learning algorithms
por: Sufriyana, Herdiantri, et al.
Publicado: (2025)

Knowledge Graphs as the Missing Data Layer for LLM-Based Industrial Asset Operations
por: Mandarapu, Madhulatha, et al.
Publicado: (2026)

Robustness of Spatio-temporal Graph Neural Networks for Fault Location in Partially Observable Distribution Grids
por: Karabulut, Burak, et al.
Publicado: (2026)

Evo-DKD: Dual-Knowledge Decoding for Autonomous Ontology Evolution in Large Language Models
por: Raman, Vishal, et al.
Publicado: (2025)

Interpretable Clustering: A Survey
por: Hu, Lianyu, et al.
Publicado: (2024)

Serverless GPU Architecture for Enterprise HR Analytics: A Production-Scale BDaaS Implementation
por: Zhang, Guilin, et al.
Publicado: (2025)

Hierarchical Robust PCA for Scalable Data Quality Monitoring in Multi-level Aggregation Pipelines
por: Ojha, Preetam Kumar
Publicado: (2025)

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure
por: Bottino, Federico, et al.
Publicado: (2026)

Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning
por: Jiang, Zeyu, et al.
Publicado: (2025)

Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings
por: Xiao, Wenxuan
Publicado: (2026)

Demand-Driven Context: A Methodology for Building Enterprise Knowledge Bases Through Agent Failure
por: Navakoti, Raj, et al.
Publicado: (2026)

Provable Fairness Repair for Deep Neural Networks
por: Ma, Jianan, et al.
Publicado: (2026)

Cold-RL: Learning Cache Eviction with Offline Reinforcement Learning for NGINX
por: Gupta, Aayush, et al.
Publicado: (2025)