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Found 5 papers, 1 papers with code
Learning Regularized Graphon Mean-Field Games with Unknown Graphons
Second, using kernel embedding of distributions, we design efficient algorithms to estimate the transition kernels, reward functions, and graphons from sampled agents.
What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization
(b) What is a proper performance metric for ICL and what is the error rate?
Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL
The cooperative Multi-A gent R einforcement Learning (MARL) with permutation invariant agents framework has achieved tremendous empirical successes in real-world applications.
Active-LATHE: An Active Learning Algorithm for Boosting the Error Exponent for Learning Homogeneous Ising Trees
We design and analyze an algorithm Active Learning Algorithm for Trees with Homogeneous Edge (Active-LATHE), which surprisingly boosts the error exponent by at least 40\% when $\rho$ is at least $0. 8$.
Robustifying Algorithms of Learning Latent Trees with Vector Variables
The optimalities of the robust version of CLRG and NJ are verified by comparing their sample complexities and the impossibility result.
