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@@ -23,7 +23,7 @@ Paris Noah's Ark Lab consists of 3 research teams that cover the following topic
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  - [Zero-shot Model-based Reinforcement Learning using Large Language Models](https://huggingface.co/papers/2410.11711): disentangled in-context learning for multivariate time series forecasting and model-based RL.
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  - [Large Language Models as Markov Chains](https://huggingface.co/papers/2410.02724): theoretical insights on their generalization and convergence properties.
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- - [A systematic study comparing hyperparameter optimization engines on tabular data](https://balazskegl.medium.com/navigating-the-maze-of-hyperparameter-optimization-insights-from-a-systematic-study-6019675ea96c) insights to navigate the maze of hyperopt techniques.
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  ### 2024
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  - [Zero-shot Model-based Reinforcement Learning using Large Language Models](https://huggingface.co/papers/2410.11711): disentangled in-context learning for multivariate time series forecasting and model-based RL.
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  - [Large Language Models as Markov Chains](https://huggingface.co/papers/2410.02724): theoretical insights on their generalization and convergence properties.
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+ - [A Systematic Study Comparing Hyperparameter Optimization Engines on Tabular Data](https://balazskegl.medium.com/navigating-the-maze-of-hyperparameter-optimization-insights-from-a-systematic-study-6019675ea96c): insights to navigate the maze of hyperopt techniques.
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  ### 2024
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