Copertina

WarpAdam: A new Adam optimizer based on Meta-Learning approach

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Pan, Chengxi, Chen, Junshang, Ye, Jingrui
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence Information Retrieval
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval
di: Li, Zihao, et al.
Pubblicazione: (2024)

LiMAML: Personalization of Deep Recommender Models via Meta Learning
di: Wang, Ruofan, et al.
Pubblicazione: (2024)

MuonRec: Shifting the Optimizer Paradigm Beyond Adam in Scalable Generative Recommendation
di: Shan, Rong, et al.
Pubblicazione: (2026)

Comparative Analysis of Novel NIRMAL Optimizer Against Adam and SGD with Momentum
di: Gaud, Nirmal, et al.
Pubblicazione: (2025)

Item Cluster-aware Prompt Learning for Session-based Recommendation
di: Yang, Wooseong, et al.
Pubblicazione: (2024)

Orchestrating Heterogeneous Experts: A Scalable MoE Framework with Anisotropy-Preserving Fusion
di: Liu, Ye, et al.
Pubblicazione: (2025)

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

RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation
di: Li, Shijun, et al.
Pubblicazione: (2026)

FinSage: A Multi-aspect RAG System for Financial Filings Question Answering
di: Wang, Xinyu, et al.
Pubblicazione: (2025)

InstructIE: A Bilingual Instruction-based Information Extraction Dataset
di: Gui, Honghao, et al.
Pubblicazione: (2023)

An Extremely Data-efficient and Generative LLM-based Reinforcement Learning Agent for Recommenders
di: Feng, Shuang, et al.
Pubblicazione: (2024)

PSLF: A PID Controller-incorporated Second-order Latent Factor Analysis Model for Recommender System
di: Wang, Jialiang, et al.
Pubblicazione: (2024)

Joint Group Profiling and Recommendation via Deep Neural Network-based Multi-Task Learning
di: Le, Ngoc Luyen, et al.
Pubblicazione: (2025)

AGRAG: Advanced Graph-based Retrieval-Augmented Generation for LLMs
di: Wang, Yubo, et al.
Pubblicazione: (2025)

Ripple Knowledge Graph Convolutional Networks For Recommendation Systems
di: Li, Chen, et al.
Pubblicazione: (2023)

Enhancing Talent Search Ranking with Role-Aware Expert Mixtures and LLM-based Fine-Grained Job Descriptions
di: Li, Jihang, et al.
Pubblicazione: (2025)

DKINet: Medication Recommendation via Domain Knowledge Informed Deep Learning
di: Liu, Sicen, et al.
Pubblicazione: (2023)

NextMem: Towards Latent Factual Memory for LLM-based Agents
di: Zhang, Zeyu, et al.
Pubblicazione: (2026)

Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
di: Chen, Mouxiang, et al.
Pubblicazione: (2023)

Learning Unified User Quantized Tokenizers for User Representation
di: He, Chuan, et al.
Pubblicazione: (2025)

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

Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
di: Han, Xiao, et al.
Pubblicazione: (2024)

A Comprehensive Survey on Deep Graph Representation Learning
di: Ju, Wei, et al.
Pubblicazione: (2023)

Beyond Predefined Schemas: TRACE-KG for Context-Enriched Knowledge Graphs from Complex Documents
di: Abolhasani, Mohammad Sadeq, et al.
Pubblicazione: (2026)

Exploring Feature-based Knowledge Distillation for Recommender System: A Frequency Perspective
di: Zhu, Zhangchi, et al.
Pubblicazione: (2024)

InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction
di: Zeng, Zhichen, et al.
Pubblicazione: (2024)

XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented Generation
di: Li, Zhuoling, et al.
Pubblicazione: (2026)

LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation
di: Jiang, Shali, et al.
Pubblicazione: (2026)

A Distance Metric Learning Model Based On Variational Information Bottleneck
di: Zhang, YaoDan, et al.
Pubblicazione: (2024)

Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study
di: Niu, Zechun, et al.
Pubblicazione: (2024)

MemoryBench: A Benchmark for Memory and Continual Learning in LLM Systems
di: Ai, Qingyao, et al.
Pubblicazione: (2025)

Joint Identifiability of Cross-Domain Recommendation via Hierarchical Subspace Disentanglement
di: Du, Jing, et al.
Pubblicazione: (2024)

Rethinking ANN-based Retrieval: Multifaceted Learnable Index for Large-scale Recommendation System
di: Zhang, Jiang, et al.
Pubblicazione: (2026)

Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction
di: Zhang, Juzheng, et al.
Pubblicazione: (2024)

A Knowledge Graph-based Retrieval-Augmented Generation Framework for Algorithm Selection in the Facility Layout Problem
di: S, Nikhil N, et al.
Pubblicazione: (2025)

Rethinking negative sampling in content-based news recommendation
di: Rebelo, Miguel Ângelo, et al.
Pubblicazione: (2024)

DiffGRM: Diffusion-based Generative Recommendation Model
di: Liu, Zhao, et al.
Pubblicazione: (2025)

A Bag of Tricks for Scaling CPU-based Deep FFMs to more than 300m Predictions per Second
di: Škrlj, Blaž, et al.
Pubblicazione: (2024)

ECAT: A Entire space Continual and Adaptive Transfer Learning Framework for Cross-Domain Recommendation
di: Hou, Chaoqun, et al.
Pubblicazione: (2024)

Industry Insights from Comparing Deep Learning and GBDT Models for E-Commerce Learning-to-Rank
di: Lutz, Yunus, et al.
Pubblicazione: (2025)