Large language models (LLMs) have shown remarkable capabilities in gener...
Over-generalization is a thorny issue in cognitive science, where people...
The difficulty of appropriately assigning credit is particularly heighte...
In multi-agent reinforcement learning, each agent acts to maximize its
i...
Interactive segmentation has recently been explored to effectively and
e...
Social dilemmas can be considered situations where individual rationalit...
Long-term time-series forecasting (LTTF) has become a pressing demand in...
With the rapid development of cloud computing, virtual machine schedulin...
Oversubscription is a common practice for improving cloud resource
utili...
Predicting medications is a crucial task in many intelligent healthcare
...
Fairness has been taken as a critical metric on machine learning models....
Multi-agent pathfinding (MAPF) has been widely used to solve large-scale...
The most recent year has witnessed the success of applying the Vision
Tr...
A novel simulator called VMAgent is introduced to help RL researchers be...
Medical image segmentation is one of the fundamental problems for artifi...
Recommending medications for patients using electronic health records (E...
Non-stationarity is one thorny issue in multi-agent reinforcement learni...
When solving a complex task, humans will spontaneously form teams and to...
Traditional centralized multi-agent reinforcement learning (MARL) algori...
Despite their success, existing meta reinforcement learning methods stil...
This work explores the large-scale multi-agent communication mechanism u...
Link failures and cable miswirings are not uncommon in building data cen...
Existing automatic 3D image segmentation methods usually fail to meet th...
Generalized zero-shot learning (GZSL) tackles the problem of learning to...
Existing traffic engineering (TE) solutions performs well for software
d...
This work investigates the problem of efficiently learning discriminativ...
Recently, convolutional neural networks (CNNs) have achieved excellent
p...
This paper proposes a novel branch-and-bound(BMWVC) algorithm to exactly...
With the development of feature extraction technique, one sample always ...