Cover Image

Uniform Loss vs. Specialized Optimization: A Comparative Analysis in Multi-Task Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gama, Gabriel S., Grassi Jr, Valdir
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DeepSeek vs. ChatGPT vs. Claude: A Comparative Study for Scientific Computing and Scientific Machine Learning Tasks
by: Jiang, Qile, et al.
Published: (2025)

Comparing Contrastive and Triplet Loss: Variance Analysis and Optimization Behavior
by: Zeng, Donghuo
Published: (2025)

Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective
by: Phan, Hoang, et al.
Published: (2022)

Continual Optimization with Symmetry Teleportation for Multi-Task Learning
by: Zhou, Zhipeng, et al.
Published: (2025)

MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimization
by: Faez, Faezeh, et al.
Published: (2024)

Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
by: Byun, Ju-Seung, et al.
Published: (2024)

Dataset Distribution Impacts Model Fairness: Single vs. Multi-Task Learning
by: Raumanns, Ralf, et al.
Published: (2024)

Multi-Objective Optimization for Sparse Deep Multi-Task Learning
by: Hotegni, S. S., et al.
Published: (2023)

Collaborative Multi-LoRA Experts with Achievement-based Multi-Tasks Loss for Unified Multimodal Information Extraction
by: Yuan, Li, et al.
Published: (2025)

Task Scheduling & Forgetting in Multi-Task Reinforcement Learning
by: Speckmann, Marc, et al.
Published: (2025)

Task Addition in Multi-Task Learning by Geometrical Alignment
by: Yim, Soorin, et al.
Published: (2024)

Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP
by: Pan, Yuxin, et al.
Published: (2025)

Comparative Analysis of MDL-VAE vs. Standard VAE on 202 Years of Gynecological Data
by: Santos, Paula
Published: (2025)

Analytical Uncertainty-Based Loss Weighting in Multi-Task Learning
by: Kirchdorfer, Lukas, et al.
Published: (2024)

Nirvana: A Specialized Generalist Model With Task-Aware Memory Mechanism
by: Jiang, Yuhua, et al.
Published: (2025)

Multi-Task Learning with Multi-Annotation Triplet Loss for Improved Object Detection
by: Zhou, Meilun, et al.
Published: (2025)

In-Context Learning in Linear vs. Quadratic Attention Models: An Empirical Study on Regression Tasks
by: Goel, Ayush, et al.
Published: (2026)

Dual-Balancing for Multi-Task Learning
by: Lin, Baijiong, et al.
Published: (2023)

Efficient Multi-Task Reinforcement Learning with Cross-Task Policy Guidance
by: He, Jinmin, et al.
Published: (2025)

Landscaper: Understanding Loss Landscapes Through Multi-Dimensional Topological Analysis
by: Chen, Jiaqing, et al.
Published: (2026)

RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning Tasks
by: Tulchinskii, Eduard, et al.
Published: (2025)

Minimizing Surrogate Losses for Decision-Focused Learning using Differentiable Optimization
by: Mandi, Jayanta, et al.
Published: (2025)

In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning
by: Terekhov, Mikhail, et al.
Published: (2024)

Multi-Objective Loss Balancing for Physics-Informed Deep Learning
by: Bischof, Rafael, et al.
Published: (2021)

Scale-Adaptive Power Flow Analysis with Local Topology Slicing and Multi-Task Graph Learning
by: Li, Yongzhe, et al.
Published: (2026)

Injecting Imbalance Sensitivity for Multi-Task Learning
by: Zhou, Zhipeng, et al.
Published: (2025)

Group Fairness in Multi-Task Reinforcement Learning
by: Song, Kefan, et al.
Published: (2025)

A Multi-Task Learning Approach to Linear Multivariate Forecasting
by: Nochumsohn, Liran, et al.
Published: (2025)

Task-Aware Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning
by: Fan, Ziqing, et al.
Published: (2024)

MAESTRO: Multi-Agent Environment Shaping through Task and Reward Optimization
by: Wu, Boyuan
Published: (2025)

Multi-Task Reinforcement Learning Enables Parameter Scaling
by: McLean, Reginald, et al.
Published: (2025)

HGMP:Heterogeneous Graph Multi-Task Prompt Learning
by: Jiao, Pengfei, et al.
Published: (2025)

Sparsity-Driven Plasticity in Multi-Task Reinforcement Learning
by: Todorov, Aleksandar, et al.
Published: (2025)

Multi-Task Reward Learning from Human Ratings
by: Wu, Mingkang, et al.
Published: (2025)

Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning
by: Schnitzer, Yannik, et al.
Published: (2026)

Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator
by: Watanabe, Shuhei, et al.
Published: (2022)

Multi-Task Optimization over Networks of Tasks
by: Hatzky, Julian, et al.
Published: (2026)

Projected Task-Specific Layers for Multi-Task Reinforcement Learning
by: Roberts, Josselin Somerville, et al.
Published: (2023)

Encoder vs Decoder: Comparative Analysis of Encoder and Decoder Language Models on Multilingual NLU Tasks
by: Nielsen, Dan Saattrup, et al.
Published: (2024)

A Hybrid Modeling Framework for Crop Prediction Tasks via Dynamic Parameter Calibration and Multi-Task Learning
by: Solow, William, et al.
Published: (2026)