This paper shows that sub-dictionaries sampled from a coherent dictionary using a coherence rejective Poisson sampling model are well-conditioned with high probability, as long as their expected size…

This paper introduces the Distributed Truncated Spectral Transform (DTST) for Fourier Neural Operators (FNOs), achieving significant speedups in distributed computing.

This paper improves transformer attention in character-level language modeling by applying FFT-based spectral preprocessing to learned query-key projections.

The paper demonstrates that for FFT-based radar imaging on Apple Silicon, the limiting factor for half-precision (FP16) is dynamic range, not mantissa precision, and proposes a block-floating-point (B…

This paper identifies scattering network architectures that maximize separation capacity for data with low intrinsic dimension by characterizing and bounding the separation capacity of general feature…

This paper proposes Spiking Fourier Graph Operators (SpikF-GO) for multivariate time series forecasting using Spiking Neural Networks (SNNs), introducing Hard Concrete frequency gates and Complex LIF…

This paper proposes the RFFBCGA algorithm, a random Fourier feature based bias-compensated filter that mitigates input noise interference and enhances robustness in nonlinear adaptive filtering.

This paper analyzes the statistical and computational limits of learning bounded linear operators between Sobolev spaces from noisy data, and constructs a finite-resolution blockwise least-squares est…

The paper introduces Dual-Spectral Flow Matching (DSFM), a novel generative framework that uses wavelet and cosine transforms to synthesize highly realistic, non-stationary fMRI time series for improv…

The paper describes how to compute singular value soft-thresholding using matrix polar decomposition for faster GPU processing.

This paper proves conditions for efficiently approximating expectations of certain functions with respect to standard Gaussian or symmetric exponential probability measures.

This paper simplifies the proof of the bound on the target dimension for reducing the dimension of high-dimensional polygonal curves using random projections, extending it to various distance measures…

This paper uses ergodic theory to study statistical properties of smooth sequences over the odd alphabet {1,3}, defining a notion of type for those sequences and proving unique ergodicity for subshift…

This paper identifies and quantifies two structural bottlenecks in certain state-of-the-art neural audio models that limit access to frequency-localized primitives, and proposes a lightweight interven…

This paper introduces Distributional Random Forests, which replace mean-based CART splitting with criteria that compare full conditional response distributions in candidate children. The authors syste…