1 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning
Shiji Zhou, Kunlin Lyu, Lei Zhang +2
Multi-objective optimization (MOO) has demonstrated significant success in multi-task learning by mitigating task conflicts through gradient manipulation. However, most existing me…
Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning
Tianchi Cai, Jiyan Jiang, Wenpeng Zhang +7
We study the budget allocation problem in online marketing campaigns that utilize previously collected offline data. We first discuss the long-term effect of optimizing marketing b…
Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems
Tianchi Cai, Shenliao Bao, Jiyan Jiang +5
Model-free RL-based recommender systems have recently received increasing research attention due to their capability to handle partial feedback and long-term rewards. However, most…
Algorithms and Theory for Supervised Gradual Domain Adaptation
Jing Dong, Shiji Zhou, Baoxiang Wang +1
The phenomenon of data distribution evolving over time has been observed in a range of applications, calling the needs of adaptive learning algorithms. We thus study the problem of…
Online Continual Adaptation with Active Self-Training
Shiji Zhou, Han Zhao, Shanghang Zhang +4
Models trained with offline data often suffer from continual distribution shifts and expensive labeling in changing environments. This calls for a new online learning paradigm wher…