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On the Estimation of Linear Softmax Parametrized Markov Chains
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Kunwoo Na, Junghyun Lee, Se-Young Yun
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On the Estimation of Linear Softmax Parametrized Markov Chains
Empirical Analyses of Corruption in the Clustering of Block MDPs
We show that a simple trick of randomly corrupting the trajectories in Block MDPs allow for us to use the the clustering algorithm proposed of Jedra et al. (2023) for general classes of MDPs.
Junghyun Lee, Se-Young Yun
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Empirical Analyses of Corruption in the Clustering of Block MDPs
On the Estimation of Linear Softmax Parametrized Probability Distributions
Linear softmax parametrization (LSP) of a discrete probability distribution is ubiquitous in many areas, such as deep learning, RL, …
Murad Aghazada, Mohammed Bennabbassi, Junghyun Lee, Se-Young Yun
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On the Estimation of Linear Softmax Parametrized Probability Distributions
Preliminary Empirical Analyses of Clustering in Block MDPs
We empirically validate the clustering algorithm proposed in (Jedra et al., 2022).
Junghyun Lee, Se-Young Yun
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Preliminary Empirical Analyses of Clustering in Block MDPs
A Statistical Analysis of Stochastic Gradient Noises for GNNs
Inspired from (Wang et al., ICLR'22), we provide a preliminary statistical analysis of stochastic gradient noises (SGNs) of GIN and GCN in Cora node classification task.
Junghyun Lee, Minchan Jeong, Namgyu Ho, Se-Young Yun
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A Statistical Analysis of Stochastic Gradient Noises for GNNs