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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

Trend · papers per month

count% of corpus
0.3%0.5%0.8%0.1% · Nov 202219922001200920172026
4 results for “self-consistent-field”
A Self-consistent-field Iteration for Orthogonal Canonical Correlation Analysiscs.LG

Efficient algorithm for orthogonal canonical correlation analysis (OCCA).

problem Solving the OCCA problem with orthogonality constraints.
method Sub-maximization problem with self-consistent-field (SCF) iteration for trace-fractional structure and orthogonal linear projections.
result Proposed algorithm converges globally to a KKT point and is more efficient.
orthogonal canonical correlation analysisself-consistent-fieldtrace-fractional maximizationalternating numerical schemeglobal convergence
2019-09-25abs ↗pdf ↗
Anticipatory Reinforcement Learning: From Generative Path-Laws to Distributional Value Functionscs.LG

ARL bridges non-Markovian decision processes with reinforcement learning, improving foresight and stability.

problem Inaccurate foresight in non-Markovian environments due to state-based methods' limitations.
method Lifted state space into a signature-augmented manifold, using a self-consistent field approach to anticipate future path-law.
result ARL achieves deterministic evaluation of expected returns with reduced computational complexity and variance.
Reinforcement LearningNon-Markovian ProcessesPath-LawSignature ManifoldSelf-Consistent Field
2026-04-06abs ↗pdf ↗
A Bi-level Nonlinear Eigenvector Algorithm for Wasserstein Discriminant Analysisstat.ML

A new algorithm improves Wasserstein discriminant analysis for better data classification.

problem Improving data classification in machine learning.
method Bi-level nonlinear eigenvector algorithm (WDA-nepv) for optimal transport and trace ratio optimizations.
result WDA-nepv enhances classification accuracy and scalability.
Wasserstein discriminant analysisbi-level optimizationoptimal transportself-consistent fieldtrace ratio
2022-11-21abs ↗pdf ↗
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networksstat.ML

Analyzes feature learning in neural networks using a self-consistent dynamical field theory.

problem Feature learning in infinite-width neural networks.
method Constructs deterministic dynamical order parameters as inner-product kernels for hidden unit activations and gradients.
result Reveals the hidden layer activation distribution, neural tangent kernel evolution, and output predictions.
neural networksfeature learninginfinite-widthgradient flowself-consistent field theory
2022-05-19abs ↗pdf ↗