89 citations · 302 across the 30 of their papers we have counts for
6 papers · 1 filter
Machine learning spatio-temporal epidemiological model to evaluate Germany-county-level COVID-19 risk
Lingxiao Wang, Tian Xu, Till Hannes Stoecker +3
As the COVID-19 pandemic continues to ravage the world, it is of critical significance to provide a timely risk prediction of the COVID-19 in multi-level. To implement it and evalu…
Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning
Chenjia Bai, Peng Liu, Kaiyu Liu +3
Efficient exploration remains a challenging problem in reinforcement learning, especially for tasks where extrinsic rewards from environments are sparse or even totally disregarded…
On the Global Optimality of Model-Agnostic Meta-Learning
Lingxiao Wang, Qi Cai, Zhuoran Yang +1
Model-agnostic meta-learning (MAML) formulates meta-learning as a bilevel optimization problem, where the inner level solves each subtask based on a shared prior, while the outer l…
Provably Efficient Causal Reinforcement Learning with Confounded Observational Data
Lingxiao Wang, Zhuoran Yang, Zhaoran Wang
Empowered by expressive function approximators such as neural networks, deep reinforcement learning (DRL) achieves tremendous empirical successes. However, learning expressive func…
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning
Lingxiao Wang, Zhuoran Yang, Zhaoran Wang
Multi-agent reinforcement learning (MARL) achieves significant empirical successes. However, MARL suffers from the curse of many agents. In this paper, we exploit the symmetry of a…
Revisiting Membership Inference Under Realistic Assumptions
Bargav Jayaraman, Lingxiao Wang, Katherine Knipmeyer +2
We study membership inference in settings where some of the assumptions typically used in previous research are relaxed. First, we consider skewed priors, to cover cases such as wh…