research
∙
06/15/2023
Temporally-Extended Prompts Optimization for SAM in Interactive Medical Image Segmentation
The Segmentation Anything Model (SAM) has recently emerged as a foundati...
share
research
∙
06/08/2023
Negotiated Reasoning: On Provably Addressing Relative Over-Generalization
Over-generalization is a thorny issue in cognitive science, where people...
research
∙
05/18/2023
Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning
The difficulty of appropriately assigning credit is particularly heighte...
research
∙
05/10/2023
Learning Optimal "Pigovian Tax" in Sequential Social Dilemmas
In multi-agent reinforcement learning, each agent acts to maximize its i...
research
∙
03/24/2023
CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesis
MRI synthesis promises to mitigate the challenge of missing MRI modality...
research
∙
03/19/2023
Boundary-aware Supervoxel-level Iteratively Refined Interactive 3D Image Segmentation with Multi-agent Reinforcement Learning
Interactive segmentation has recently been explored to effectively and e...
research
∙
01/31/2023
Learning Roles with Emergent Social Value Orientations
Social dilemmas can be considered situations where individual rationalit...
research
∙
01/28/2023
Decentralized Entropic Optimal Transport for Privacy-preserving Distributed Distribution Comparison
Privacy-preserving distributed distribution comparison measures the dist...
research
∙
11/29/2022
ReAssigner: A Plug-and-Play Virtual Machine Scheduling Intensifier for Heterogeneous Requests
With the rapid development of cloud computing, virtual machine schedulin...
research
∙
11/21/2022
Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning
Oversubscription is a common practice for improving cloud resource utili...
research
∙
02/09/2022
Obtaining Dyadic Fairness by Optimal Transport
Fairness has been taken as a critical metric on machine learning models....
research
∙
02/08/2022
Multi-Agent Path Finding with Prioritized Communication Learning
Multi-agent pathfinding (MAPF) has been widely used to solve large-scale...
research
∙
12/09/2021
VMAgent: Scheduling Simulator for Reinforcement Learning
A novel simulator called VMAgent is introduced to help RL researchers be...
research
∙
11/15/2021
Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration
Medical image segmentation is one of the fundamental problems for artifi...
research
∙
02/21/2021
Dealing with Non-Stationarity in Multi-Agent Reinforcement Learning via Trust Region Decomposition
Non-stationarity is one thorny issue in multi-agent reinforcement learni...
research
∙
02/09/2021
Structured Diversification Emergence via Reinforced Organization Control and Hierarchical Consensus Learning
When solving a complex task, humans will spontaneously form teams and to...
research
∙
06/28/2020
FDA3 : Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications
Along with the proliferation of Artificial Intelligence (AI) and Interne...
research
∙
04/17/2020
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning
Traditional centralized multi-agent reinforcement learning (MARL) algori...
research
∙
02/11/2020
Hyper-Meta Reinforcement Learning with Sparse Reward
Despite their success, existing meta reinforcement learning methods stil...
research
∙
02/11/2020
Learning Structured Communication for Multi-agent Reinforcement Learning
This work explores the large-scale multi-agent communication mechanism u...
research
∙
11/23/2019
Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning
Existing automatic 3D image segmentation methods usually fail to meet th...
research
∙
11/20/2019
Heterogeneous Graph-based Knowledge Transfer for Generalized Zero-shot Learning
Generalized zero-shot learning (GZSL) tackles the problem of learning to...
research
∙
02/12/2018