Copertina

Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Hubert, Nicolas, Monnin, Pierre, Brun, Armelle, Monticolo, Davy
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Do Similar Entities have Similar Embeddings?
di: Hubert, Nicolas, et al.
Pubblicazione: (2023)

PyGraft: Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
di: Hubert, Nicolas, et al.
Pubblicazione: (2023)

Unsupervised Learning Method for the Wave Equation Based on Finite Difference Residual Constraints Loss
di: Feng, Xin, et al.
Pubblicazione: (2024)

Contrastive Difference Predictive Coding
di: Zheng, Chongyi, et al.
Pubblicazione: (2023)

G2CP: A Graph-Grounded Communication Protocol for Verifiable and Efficient Multi-Agent Reasoning
di: Khaled, Karim Ben, et al.
Pubblicazione: (2026)

Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs
di: Wang, Yilong, et al.
Pubblicazione: (2025)

Thinking in Different Spaces: Domain-Specific Latent Geometry Survives Cross-Architecture Translation
di: Armstrong, Marcus, et al.
Pubblicazione: (2026)

Multi-Relational Graph Neural Network for Out-of-Domain Link Prediction
di: Sattar, Asma, et al.
Pubblicazione: (2024)

STARC: A General Framework For Quantifying Differences Between Reward Functions
di: Skalse, Joar, et al.
Pubblicazione: (2023)

AI to Identify Strain-sensitive Regions of the Optic Nerve Head Linked to Functional Loss in Glaucoma
di: Chuangsuwanich, Thanadet, et al.
Pubblicazione: (2025)

Direct Distillation between Different Domains
di: Tang, Jialiang, et al.
Pubblicazione: (2024)

Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize
di: Shah, Sanket, et al.
Pubblicazione: (2023)

Temporal Difference Flows
di: Farebrother, Jesse, et al.
Pubblicazione: (2025)

Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
di: Shirakawa, Toru, et al.
Pubblicazione: (2024)

Scaling Session-Based Transformer Recommendations using Optimized Negative Sampling and Loss Functions
di: Wilm, Timo, et al.
Pubblicazione: (2023)

Disentanglement in Difference: Directly Learning Semantically Disentangled Representations by Maximizing Inter-Factor Differences
di: Zhang, Xingshen, et al.
Pubblicazione: (2025)

Enhancing Link Prediction with Fuzzy Graph Attention Networks and Dynamic Negative Sampling
di: Xing, Jinming, et al.
Pubblicazione: (2024)

Extreme-value forest fire prediction A study of the Loss Function in an Ordinality Scheme
di: Caron, Nicolas, et al.
Pubblicazione: (2026)

Performance Comparison of Different Machine Learning Algorithms on the Prediction of Wind Turbine Power Generation
di: Eyecioglu, Onder, et al.
Pubblicazione: (2021)

PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models
di: Deng, Fei, et al.
Pubblicazione: (2024)

Discerning Temporal Difference Learning
di: Ma, Jianfei
Pubblicazione: (2023)

Backstepping Temporal Difference Learning
di: Lim, Han-Dong, et al.
Pubblicazione: (2023)

Pairwise Difference Learning for Classification
di: Belaid, Mohamed Karim, et al.
Pubblicazione: (2024)

Koopman Invariants as Drivers of Emergent Time-Series Clustering in Joint-Embedding Predictive Architectures
di: Ruiz-Morales, Pablo, et al.
Pubblicazione: (2025)

Reaction Prediction via Interaction Modeling of Symmetric Difference Shingle Sets
di: Shi, Runhan, et al.
Pubblicazione: (2025)

Sampling and Loss Weights in Multi-Domain Training
di: Salmani, Mahdi, et al.
Pubblicazione: (2025)

Robust Real-Time Mortality Prediction in the Intensive Care Unit using Temporal Difference Learning
di: Frost, Thomas, et al.
Pubblicazione: (2024)

Temporal-Difference Variational Continual Learning
di: Melo, Luckeciano C., et al.
Pubblicazione: (2024)

Mathematical Framing for Different Agent Strategies
di: Stephens, Philip, et al.
Pubblicazione: (2025)

Gradient Iterated Temporal-Difference Learning
di: Vincent, Théo, et al.
Pubblicazione: (2026)

Evaluation of Bio-Inspired Models under Different Learning Settings For Energy Efficiency in Network Traffic Prediction
di: Tsiolakis, Theodoros, et al.
Pubblicazione: (2024)

Adaptive Weighted Loss for Sequential Recommendations on Sparse Domains
di: Mittal, Akshay, et al.
Pubblicazione: (2025)

KGPrune: a Web Application to Extract Subgraphs of Interest from Wikidata with Analogical Pruning
di: Monnin, Pierre, et al.
Pubblicazione: (2024)

I Know Therefore I Score: Label-Free Crafting of Scoring Functions using Constraints Based on Domain Expertise
di: Palakkadavath, Ragja, et al.
Pubblicazione: (2022)

Meta-Learning Adaptive Loss Functions
di: Raymond, Christian, et al.
Pubblicazione: (2023)

Demystifying the Recency Heuristic in Temporal-Difference Learning
di: Daley, Brett, et al.
Pubblicazione: (2024)

Structural Alignment in Link Prediction
di: Sardina, Jeffrey Seathrún
Pubblicazione: (2025)

Link Prediction with Relational Hypergraphs
di: Huang, Xingyue, et al.
Pubblicazione: (2024)

Reevaluation of Inductive Link Prediction
di: Ott, Simon, et al.
Pubblicazione: (2024)

Instance Discrimination for Link Prediction
di: Cuzin-Rambaud, Valentin, et al.
Pubblicazione: (2026)