Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..

The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium

Authors: Ian Gemp, Charlie Chen, Brian McWilliams

ICLR 2023 | Venue PDF | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Empirically we demonstrate that this resulting algorithm is able to solve a variety of SGEP problem instances including a large-scale analysis of neural network activations.
Researcher Affiliation Industry EMAIL Charlie Chen EMAIL Brian Mc Williams Google Research Z urich, Switzerland EMAIL
Pseudocode Yes Algorithm 1 Deterministic / Full-batch γ-Eigen Game; Algorithm 2 Stochastic γ-Eigen Game
Open Source Code Yes A Jax implementation is available at github.com/deepmind/eigengame.
Open Datasets Yes We replicate a synthetic experiment from scikit-learn(Pedregosa et al., 2011) and compare Algorithm 2 to several approaches... loading minibatches of CIFAR-10 images, running them through a deep convolutional network, harvesting the activations, and then passing them to our distributed γ-Eigen Game solver.
Dataset Splits No The paper mentions using minibatches and datasets like CIFAR-10, but it does not specify explicit training, validation, or test dataset splits (e.g., 80/10/10 percentages or sample counts).
Hardware Specification Yes Figure 4 demonstrates our approach (parallelized over 8 TPU chips)
Software Dependencies No The paper mentions using 'Jax', 'Scipy's linalg.eigh(A, B)', and 'scikit-learn', but it does not provide specific version numbers for these software components.
Experiment Setup Yes Hyperparameters are listed in Appx. H.