Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective

27 August 2023

Papers citing "Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective"

9 / 9 papers shown

Title
In-Context Adaptation to Concept Drift for Learned Database Operations Jiaqi Zhu Shaofeng Cai Yanyan Shen Gang Chen Fang Deng Beng Chin Ooi VLM 40 0 0 07 May 2025
Federated Communication-Efficient Multi-Objective Optimization Baris Askin Pranay Sharma Gauri Joshi Carlee Joe-Wong FedML 46 1 0 21 Oct 2024
SGW-based Multi-Task Learning in Vision Tasks Ruiyuan Zhang Yuyao Chen Yuchi Huo Jiaxiang Liu Dianbing Xi Jie Liu Chao Wu 26 0 0 03 Oct 2024
Enhancing Domain Adaptation through Prompt Gradient Alignment Hoang Phan Lam C. Tran Quyen Tran Trung Le 47 0 0 13 Jun 2024
Fairness-Aware Meta-Learning via Nash Bargaining Yi Zeng Xuelin Yang Li Chen Cristian Canton Ferrer Ming Jin Michael I. Jordan Ruoxi Jia 19 2 0 11 Jun 2024
Understanding Optimal Feature Transfer via a Fine-Grained Bias-Variance Analysis Yufan Li Subhabrata Sen Ben Adlam MLT 23 1 0 18 Apr 2024
Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards Haoxiang Wang Yong Lin Wei Xiong Rui Yang Shizhe Diao Shuang Qiu Han Zhao Tong Zhang 34 70 0 28 Feb 2024
Do Current Multi-Task Optimization Methods in Deep Learning Even Help? Derrick Xin Behrooz Ghorbani Ankush Garg Orhan Firat Justin Gilmer MoMe 67 61 0 23 Sep 2022
Controllable Pareto Multi-Task Learning Xi Lin Zhiyuan Yang Qingfu Zhang Sam Kwong MoE 61 72 0 13 Oct 2020