A triplet-based plateau search algorithm is proposed to adaptively determine a near-minimal number of trees for random forests by monitoring relative OOB score changes across forest size triplets, removing n_trees from the TPE search space.
Hyperparameter Optimization: Foundations, Algorithms, Best Practices, and Open Challenges
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RAMP introduces an adaptive scalar denoiser in the AMP framework for low-complexity discrete-aware detection in overloaded MIMO, closely matching IDLS performance while avoiding standard AMP failure.
rush introduces a shared-state coordination layer for asynchronous distributed iterative algorithms in R via Redis, with integration to mlr3 and a demonstration on decentralized Bayesian optimization for LightGBM tuning across four datasets with 448 workers.
Large-scale neutral benchmark of survival models on low-dimensional right-censored data finds Cox PH performs comparably to more complex methods across discrimination, calibration, and predictive metrics.
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Regularized Approximate Message Passing for Overloaded Discrete Linear Inversion
RAMP introduces an adaptive scalar denoiser in the AMP framework for low-complexity discrete-aware detection in overloaded MIMO, closely matching IDLS performance while avoiding standard AMP failure.
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rush: Scalable Asynchronous Distributed Computing via Shared State in R
rush introduces a shared-state coordination layer for asynchronous distributed iterative algorithms in R via Redis, with integration to mlr3 and a demonstration on decentralized Bayesian optimization for LightGBM tuning across four datasets with 448 workers.
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A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional Data
Large-scale neutral benchmark of survival models on low-dimensional right-censored data finds Cox PH performs comparably to more complex methods across discrimination, calibration, and predictive metrics.