MONET represents tasks as graph nodes and uses neighbor-based crossover plus per-task mutation to transfer knowledge, matching or exceeding MAP-Elites performance on four large-scale simulation domains.
Graphical models for processing missing data
6 Pith papers cite this work. Polarity classification is still indexing.
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A Fréchet-based random-effects algorithm with M-estimation consistency guarantees is proposed for modeling non-Euclidean random objects in general metric spaces.
The Wilcoxon signed-rank test routinely loses Type I error control in IR benchmarking and should be abandoned.
Single-seed CRPS estimates in limited-data BDL show high variance and peaks for heteroscedastic methods, with local variance correlating above 0.96 to single-seed error.
The paper proposes and analyzes a distributed perception mechanism in Friedkin-Johnsen networks that enables convergence to true social power through local interactions in static and reflected-appraisal settings.
Complete-case TMLE that includes an outcome-missingness model shows lower bias and greater robustness to positivity violations than multiple imputation approaches, while MI with CART yields lower RMSE and nominal coverage in simulations based on five missingness DAGs and a real epidemiological data.
citing papers explorer
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Multi-Task Optimization over Networks of Tasks
MONET represents tasks as graph nodes and uses neighbor-based crossover plus per-task mutation to transfer knowledge, matching or exceeding MAP-Elites performance on four large-scale simulation domains.
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Random-Effects Algorithm for Random Objects in Metric Spaces
A Fréchet-based random-effects algorithm with M-estimation consistency guarantees is proposed for modeling non-Euclidean random objects in general metric spaces.
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Stop Using the Wilcoxon Test: Myth, Misconception and Misuse in IR Research
The Wilcoxon signed-rank test routinely loses Type I error control in IR benchmarking and should be abandoned.
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A Tale of Two Variances: When Single-Seed Benchmarks Fail in Bayesian Deep Learning
Single-seed CRPS estimates in limited-data BDL show high variance and peaks for heteroscedastic methods, with local variance correlating above 0.96 to single-seed error.
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Dynamical models for distributed social power perception in Friedkin-Johnsen influence networks
The paper proposes and analyzes a distributed perception mechanism in Friedkin-Johnsen networks that enables convergence to true social power through local interactions in static and reflected-appraisal settings.
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Causal Effect Estimation with TMLE: Handling Missing Data and Near-Violations of Positivity
Complete-case TMLE that includes an outcome-missingness model shows lower bias and greater robustness to positivity violations than multiple imputation approaches, while MI with CART yields lower RMSE and nominal coverage in simulations based on five missingness DAGs and a real epidemiological data.