Image de couverture de livre

Interpretable Multi-task Learning with Shared Variable Embeddings

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Żelaszczyk, Maciej, Mańdziuk, Jacek
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Text-to-Image Cross-Modal Generation: A Systematic Review
par: Żelaszczyk, Maciej, et autres
Publié: (2024)

Multi-Label Contrastive Learning for Abstract Visual Reasoning
par: Małkiński, Mikołaj, et autres
Publié: (2020)

Bootstrap Sampling Rate Greater than 1.0 May Improve Random Forest Performance
par: Kaźmierczak, Stanisław, et autres
Publié: (2024)

Modified Adaptive Tree-Structured Parzen Estimator for Hyperparameter Optimization
par: Sieradzki, Szymon, et autres
Publié: (2025)

Training chord recognition models on artificially generated audio
par: Majchrzak, Martyna, et autres
Publié: (2025)

A Unified View of Abstract Visual Reasoning Problems
par: Małkiński, Mikołaj, et autres
Publié: (2024)

A-I-RAVEN and I-RAVEN-Mesh: Two New Benchmarks for Abstract Visual Reasoning
par: Małkiński, Mikołaj, et autres
Publié: (2024)

One Self-Configurable Model to Solve Many Abstract Visual Reasoning Problems
par: Małkiński, Mikołaj, et autres
Publié: (2023)

Advancing Generalization Across a Variety of Abstract Visual Reasoning Tasks
par: Małkiński, Mikołaj, et autres
Publié: (2025)

Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matrices
par: Małkiński, Mikołaj, et autres
Publié: (2022)

Cultivating Archipelago of Forests: Evolving Robust Decision Trees through Island Coevolution
par: Żychowski, Adam, et autres
Publié: (2024)

ReModels: Quantile Regression Averaging models
par: Zakrzewski, Grzegorz, et autres
Publié: (2024)

Representation-based Broad Hallucination Detectors Fail to Generalize Out of Distribution
par: Dubanowska, Zuzanna, et autres
Publié: (2025)

Reasoning Limitations of Multimodal Large Language Models. A Case Study of Bongard Problems
par: Małkiński, Mikołaj, et autres
Publié: (2024)

Bongard-RWR+: Real-World Representations of Fine-Grained Concepts in Bongard Problems
par: Pawlonka, Szymon, et autres
Publié: (2025)

InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning
par: Bejnordi, Babak Ehteshami, et autres
Publié: (2024)

Leveraging Temporally Extended Behavior Sharing for Multi-task Reinforcement Learning
par: Lee, Gawon, et autres
Publié: (2025)

The Impact of Bootstrap Sampling Rate on Random Forest Performance in Regression Tasks
par: Iwaniuk, Michał, et autres
Publié: (2025)

Reasoning Capabilities of Large Language Models. Lessons Learned from General Game Playing
par: Świechowski, Maciej, et autres
Publié: (2026)

Multi-task Learning for Heterogeneous Data via Integrating Shared and Task-Specific Encodings
par: Sui, Yang, et autres
Publié: (2025)

Shared-unique Features and Task-aware Prioritized Sampling on Multi-task Reinforcement Learning
par: Lin, Po-Shao, et autres
Publié: (2024)

Hierarchical Structure Sharing Empowers Multi-task Heterogeneous GNNs for Customer Expansion
par: Feng, Xinyue, et autres
Publié: (2024)

STEM: Unleashing the Power of Embeddings for Multi-task Recommendation
par: Su, Liangcai, et autres
Publié: (2023)

Multi-task CNN Behavioral Embedding Model For Transaction Fraud Detection
par: Qu, Bo, et autres
Publié: (2024)

Adaptive Personalized Federated Learning via Multi-task Averaging of Kernel Mean Embeddings
par: Fermanian, Jean-Baptiste, et autres
Publié: (2026)

MS-IMAP -- A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning
par: Deutsch, Shay, et autres
Publié: (2024)

Learning Action Embeddings for Off-Policy Evaluation
par: Cief, Matej, et autres
Publié: (2023)

Monotonic Transformation Invariant Multi-task Learning
par: Murthy, Surya, et autres
Publié: (2025)

Distributed Networked Multi-task Learning
par: Hong, Lingzhou, et autres
Publié: (2024)

Multi-task Online Learning for Probabilistic Load Forecasting
par: Zaballa, Onintze, et autres
Publié: (2025)

Characterization of Transfer Using Multi-task Learning Curves
par: Millinghoffer, András, et autres
Publié: (2025)

Adaptive Multi-task Learning for Multi-sector Portfolio Optimization
par: Fan, Qingliang, et autres
Publié: (2025)

ProPML: Probability Partial Multi-label Learning
par: Struski, Łukasz, et autres
Publié: (2024)

Interpretable Multi-Source Data Fusion Through Latent Variable Gaussian Process
par: Ravi, Sandipp Krishnan, et autres
Publié: (2024)

Heterogeneous Resource Allocation with Multi-task Learning for Wireless Networks
par: Mitsiou, Nikos A., et autres
Publié: (2025)

Adaptive Multi-task Learning for Probabilistic Load Forecasting
par: Zaballa, Onintze, et autres
Publié: (2025)

Multi-task Learning for Radar Signal Characterisation
par: Huang, Zi, et autres
Publié: (2023)

Beyond instruction-conditioning, MoTE: Mixture of Task Experts for Multi-task Embedding Models
par: Romero, Miguel, et autres
Publié: (2025)

ZEUS: Zero-shot Embeddings for Unsupervised Separation of Tabular Data
par: Marszałek, Patryk, et autres
Publié: (2025)

A Large Dimensional Analysis of Multi-task Semi-Supervised Learning
par: Leger, Victor, et autres
Publié: (2024)