Cover Image

EVNextTrade: Learning-to-Rank-Based Recommendation of Next Charging Nodes for EV-EV Energy Trading

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rahmana, Md Mahfujur, Barros, Alistair, Jurdak, Raja, Koggalahewa, Darshika
Format:	Preprint
Published:	2026
Subjects:	Information Retrieval Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Ensembles at Any Cost? Accuracy-Energy Trade-offs in Recommender Systems
by: Nitschke, Jannik, et al.
Published: (2026)

LLM-Enabled EV Charging Stations Recommendation
by: Teimoori, Zeinab
Published: (2025)

Meta-Learning and Targeted Differential Privacy to Improve the Accuracy-Privacy Trade-off in Recommendations
by: Müllner, Peter, et al.
Published: (2026)

Adaptive Quality-Diversity Trade-offs for Large-Scale Batch Recommendation
by: Réda, Clémence, et al.
Published: (2026)

Efficient Pointwise-Pairwise Learning-to-Rank for News Recommendation
by: Kannen, Nithish, et al.
Published: (2024)

The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit
by: Zhou, Huixue, et al.
Published: (2025)

Pseudo Label NCF for Sparse OHC Recommendation: Dual Representation Learning and the Separability Accuracy Trade off
by: Barman, Pronob Kumar, et al.
Published: (2026)

RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendation
by: Wu, Renzhi, et al.
Published: (2025)

Efficient and Effective Query Context-Aware Learning-to-Rank Model for Sequential Recommendation
by: Dzhoha, Andrii, et al.
Published: (2025)

Correcting for Position Bias in Learning to Rank: A Control Function Approach
by: Islam, Md Aminul, et al.
Published: (2025)

RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
by: Chowdhury, Tanya, et al.
Published: (2024)

Hierarchical Group-wise Ranking Framework for Recommendation Models
by: Yan, YaChen, et al.
Published: (2025)

Probabilistic Rank and Reward: A Scalable Model for Slate Recommendation
by: Aouali, Imad, et al.
Published: (2022)

Continual Low-Rank Adapters for LLM-based Generative Recommender Systems
by: Yoo, Hyunsik, et al.
Published: (2025)

Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations
by: Singh, Anima, et al.
Published: (2023)

Dual Correction Strategy for Ranking Distillation in Top-N Recommender System
by: Lee, Youngjune, et al.
Published: (2021)

CASE: Cadence-Aware Set Encoding for Large-Scale Next Basket Repurchase Recommendation
by: Cao, Yanan, et al.
Published: (2026)

Shielded RecRL: Explanation Generation for Recommender Systems without Ranking Degradation
by: Tiwari, Ansh, et al.
Published: (2025)

Low Rank Field-Weighted Factorization Machines for Low Latency Item Recommendation
by: Shtoff, Alex, et al.
Published: (2024)

RewardRank: Optimizing True Learning-to-Rank Utility
by: Bhatt, Gaurav, et al.
Published: (2025)

Graph Hopfield Networks: Energy-Based Node Classification with Associative Memory
by: Rao, Abinav, et al.
Published: (2026)

Context Features Are Cheap: Rank-Aware Decomposition for Efficient Feature Interaction in Recommender Systems
by: Tkach, Yevgeny
Published: (2026)

Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation
by: Gomez, Camilo, et al.
Published: (2026)

Learning Time Slot Preferences via Mobility Tree for Next POI Recommendation
by: Huang, Tianhao, et al.
Published: (2024)

FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning
by: Oh, Sejoon, et al.
Published: (2024)

Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank
by: Gupta, Shashank, et al.
Published: (2024)

The Structure-Content Trade-off in Knowledge Graph Retrieval
by: Six, Valentin, et al.
Published: (2025)

Directed Criteria Citation Recommendation and Ranking Through Link Prediction
by: Watson, William, et al.
Published: (2024)

Large Language Models for Next Point-of-Interest Recommendation
by: Li, Peibo, et al.
Published: (2024)

Learning Cascade Ranking as One Network
by: Wang, Yunli, et al.
Published: (2025)

Estimating the Hessian Matrix of Ranking Objectives for Stochastic Learning to Rank with Gradient Boosted Trees
by: Kang, Jingwei, et al.
Published: (2024)

A Survey on E-Commerce Learning to Rank
by: Kabir, Md. Ahsanul, et al.
Published: (2024)

Online Learning for Recommendations at Grubhub
by: Egg, Alex
Published: (2021)

Position-Aware Sequential Attention for Accurate Next Item Recommendations
by: Nabiev, Timur, et al.
Published: (2026)

Learning to Rank with Variable Result Presentation Lengths
by: Knyazev, Norman, et al.
Published: (2025)

EasyRL4Rec: An Easy-to-use Library for Reinforcement Learning Based Recommender Systems
by: Yu, Yuanqing, et al.
Published: (2024)

DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation
by: Li, Hourun, et al.
Published: (2024)

Evaluating Cost-Accuracy Trade-offs in Multimodal Search Relevance Judgements
by: Terragni, Silvia, et al.
Published: (2024)

Review-Based Hyperbolic Cross-Domain Recommendation
by: Choi, Yoonhyuk, et al.
Published: (2024)

SocialRec: User Activity Based Post Weighted Dynamic Personalized Post Recommendation System in Social Media
by: Hossain, Ismail, et al.
Published: (2024)