MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shiftsby Renchunzi Xie, Ambroise Odonnat,…
Optimizing Vehicular Networks with Variational Quantum Circuits-based Reinforcement Learningby Zijiang Yan, Ramsundar Tanikella, Hina TabassumFirst…
Kernel Semi-Implicit Variational Inferenceby Ziheng Cheng, Longlin Yu, Tianyu Xie, Shiyue Zhang, Cheng ZhangFirst submitted…
FedMAP: Unlocking Potential in Personalized Federated Learning through Bi-Level MAP Optimizationby Fan Zhang, Carlos Esteve-Yagüe,…
Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Spaceby Minji Lee, Luiz…
Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Samplingby Danil Provodin,…
Trust the Model Where It Trusts Itself – Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaptionby Bernd…
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous mediaby Matthaios Chatzopoulos,…
Towards Standardizing AI Bias Explorationby Emmanouil Krasanakis, Symeon PapadopoulosFirst submitted to arxiv on: 29 May…
DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraintsby Andrew Zhao, Quentin Xu,…