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.
DGMM improves Gaussian mixture modeling efficiency and stability.
Diagonal linear networks converge to lasso regularization path during training.
This paper deals with the design of a sensing matrix along with a sparse recovery algorithm by utilizing the probability-based prior information for compressed sensing system. With the knowledge of the probability for each atom of the dictionary being used, a diagonal weighted matrix is obtained and then the sensing ma…
Gradient descent optimally trains RNNs without overparameterization.
Paper proves spectral sequences of knot spaces are isomorphic over fields.
Many scientific and engineering fields involve analyzing network data. For document networks, relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents, and they have shown promise on predicting network structures and discovering latent topic rep…