Fitting logic gates as 4D multilinear polynomials with covariance Jacobian selection matches or beats 16D softmax baselines on seven datasets and remains stable at 12-layer depth where the baseline drops 37 points on CIFAR-10.
Bishop.Pattern Recognition and Machine Learning
7 Pith papers cite this work. Polarity classification is still indexing.
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2026 7verdicts
UNVERDICTED 7representative citing papers
In-context learning decomposes into concept-coordinate regression plus off-subspace leakage, with recoverable task information concentrating in a 68-73 dimensional task-aligned subspace of the residual stream that restores 78.8% of the accuracy gap in Llama-3-8B experiments.
A Bayesian finite mixture of cluster-specific low-rank regressions for mixed Gaussian-Bernoulli-negative binomial outcomes, with posterior contraction results and WAIC-based tuning of clusters and rank.
A Dirichlet process mixture model for marked Poisson point processes with squared-link intensities and Laplace variational inference jointly infers clusters, cluster count, and continuous mark-specific intensity surfaces.
Self-supervised encoders prefer isotropic Gaussian latent states because the Information Bottleneck, recast as rate-distortion over the predictive manifold, makes these states optimal for target-neutral representations.
Reinforcement learning with shallow networks produces stronger Schnapsen agents than supervised imitation and yields statistically significant gains against strong search-based baselines when paired with lookahead.
Supervised LDA restructuring of PCA-compressed embeddings raises silhouette separability from near zero to 0.197 in plant phenomics but yields mixed classical ML gains and persistent challenges for quantum kernel alignment under limited compute.
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From Imitation to Interaction: Mastering Game of Schnapsen with Shallow Reinforcement Learning
Reinforcement learning with shallow networks produces stronger Schnapsen agents than supervised imitation and yields statistically significant gains against strong search-based baselines when paired with lookahead.