Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
[PDF][PDF] Mitigating gradient bias in multi-objective learning: A provably convergent approach
Machine learning problems with multiple objectives appear either i) in learning with multiple
criteria where learning has to make a trade-off between multiple performance metrics such …
criteria where learning has to make a trade-off between multiple performance metrics such …
Three-way trade-off in multi-objective learning: Optimization, generalization and conflict-avoidance
Multi-objective learning (MOL) often arises in emerging machine learning problems when
multiple learning criteria or tasks need to be addressed. Recent works have developed …
multiple learning criteria or tasks need to be addressed. Recent works have developed …
Anchor-changing regularized natural policy gradient for multi-objective reinforcement learning
We study policy optimization for Markov decision processes (MDPs) with multiple reward
value functions, which are to be jointly optimized according to given criteria such as …
value functions, which are to be jointly optimized according to given criteria such as …
Preparing for black swans: The antifragility imperative for machine learning
M ** - ar** for Acrobatic Robots: A Constrained Multi-Objective Reinforcement Learning Approach
As the complexity of tasks addressed through reinforcement learning (RL) increases, the
definition of reward functions also has become highly complicated. We introduce an RL …
definition of reward functions also has become highly complicated. We introduce an RL …
Risk-sensitive bayesian games for multi-agent reinforcement learning under policy uncertainty
In stochastic games with incomplete information, the uncertainty is evoked by the lack of
knowledge about a player's own and the other players' types, ie the utility function and the …
knowledge about a player's own and the other players' types, ie the utility function and the …
C-MORL: Multi-Objective Reinforcement Learning through Efficient Discovery of Pareto Front
Multi-objective reinforcement learning (MORL) excels at handling rapidly changing
preferences in tasks that involve multiple criteria, even for unseen preferences. However …
preferences in tasks that involve multiple criteria, even for unseen preferences. However …
Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond
Multi-objective optimization (MOO) in deep learning aims to simultaneously optimize
multiple conflicting objectives, a challenge frequently encountered in areas like multi-task …
multiple conflicting objectives, a challenge frequently encountered in areas like multi-task …