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We present random sampling procedures for Motzkin and Schr\"oder paths, following previous work on Dyck paths. Our algorithms follow the anticipated rejection method of the Florentine algorithms (Barcucci et al. 1994+), but introduce a…

Data Structures and Algorithms · Computer Science 2018-03-15 Axel Bacher

Fast Fourier Transforms (FFT) are widely used to reduce memory and computational costs in deep learning. However, existing implementations, including standard FFT and real FFT (rFFT), cannot achieve true in-place computation. In particular,…

Machine Learning · Computer Science 2025-12-23 Xinyu Ding , Bangtian Liu , Siyu Liao , Zhongfeng Wang

We introduce an efficient combination of polyhedral analysis and predicate partitioning. Template polyhedral analysis abstracts numerical variables inside a program by one polyhedron per control location, with a priori fixed directions for…

Logic in Computer Science · Computer Science 2014-10-06 David Monniaux , Peter Schrammel

The main goal of this paper is to achieve a simultaneous treatment of the even and odd truncated matricial Hamburger moment problems in the most general case. In the odd case, these results are completely new for the matrix case, whereas…

Complex Variables · Mathematics 2012-07-31 Bernd Fritzsche , Bernd Kirstein , Conrad Mädler

To address limitations of the graph fractional Fourier transform (GFRFT) Wiener filtering and the traditional joint time-vertex fractional Fourier transform (JFRFT) Wiener filtering, this study proposes a filtering method based on the…

Signal Processing · Electrical Eng. & Systems 2025-07-30 Ziqi Yan , Zhichao Zhang

A study of alternative transforms to FFT in order to compare their potential to enhance resolution and computation time in the framework of THz time domain spectroscopy (THz-TDS) instruments is carried out. Both from simulated and…

Signal Processing · Electrical Eng. & Systems 2021-08-10 Abel Garcia-Devesa , Miguel A Baez-Chorro , Borja Vidal

The matrix inversion is an interesting topic in algebra mathematics. However, to determine an inverse matrix from a given matrix is required many computation tools and time resource if the size of matrix is huge. In this paper, we have…

Discrete Mathematics · Computer Science 2017-08-28 Thuan Nguyen

Graph convolutional networks (GCNs) are becoming increasingly popular as they can process a wide variety of data formats that prior deep neural networks cannot easily support. One key challenge in designing hardware accelerators for GCNs is…

Machine Learning · Computer Science 2023-01-25 Mingi Yoo , Jaeyong Song , Hyeyoon Lee , Jounghoo Lee , Namhyung Kim , Youngsok Kim , Jinho Lee

This paper describes a generic algorithm for concurrent resizing and on-demand per-bucket rehashing for an extensible hash table. In contrast to known lock-based hash table algorithms, the proposed algorithm separates the resizing and…

Data Structures and Algorithms · Computer Science 2015-09-09 Anton Malakhov

We give a new probabilistic algorithm for interpolating a "sparse" polynomial f given by a straight-line program. Our algorithm constructs an approximation f* of f, such that their difference probably has at most half the number of terms of…

Symbolic Computation · Computer Science 2014-01-24 Andrew Arnold , Mark Giesbrecht , Daniel S. Roche

Nonnegative matrix factorization (NMF) has an established reputation as a useful data analysis technique in numerous applications. However, its usage in practical situations is undergoing challenges in recent years. The fundamental factor…

Machine Learning · Computer Science 2016-05-04 Mariano Tepper , Guillermo Sapiro

Scalable Gaussian Process methods are computationally attractive, yet introduce modeling biases that require rigorous study. This paper analyzes two common techniques: early truncated conjugate gradients (CG) and random Fourier features…

Machine Learning · Computer Science 2021-06-30 Andres Potapczynski , Luhuan Wu , Dan Biderman , Geoff Pleiss , John P. Cunningham

Vertex-frequency analysis, particularly the windowed graph Fourier transform (WGFT), is a significant challenge in graph signal processing. Tight frame theories is known for its low computational complexity in signal reconstruction, while…

Signal Processing · Electrical Eng. & Systems 2024-12-31 Linbo Shang , Zhichao Zhang

We consider the problem of approximating a truncated Gaussian kernel using Fourier (trigonometric) functions. The computation-intensive bilateral filter can be expressed using fast convolutions by applying such an approximation to its range…

Image and Video Processing · Electrical Eng. & Systems 2018-11-07 Sanjay Ghosh , Pravin Nair , Kunal N. Chaudhury

In this paper, we investigate unconstrained and constrained sample-based federated optimization, respectively. For each problem, we propose a privacy preserving algorithm using stochastic successive convex approximation (SSCA) techniques,…

Machine Learning · Computer Science 2021-03-18 Chencheng Ye , Ying Cui

This is a summarized follow up of the unconditional security and quadratic time O(n^2) efficiency of ZK111.

Cryptography and Security · Computer Science 2012-10-19 Zaryab Khan

Affine forms are a common way to represent convex sets of $\mathbb{R}$ using a base of error terms $\epsilon \in [-1, 1]^m$. Quadratic forms are an extension of affine forms enabling the use of quadratic error terms $\epsilon_i \epsilon_j$.…

Logic in Computer Science · Computer Science 2015-03-31 Assalé Adjé , Pierre-Loïc Garoche , Alexis Werey

Many interesting and fundamentally practical optimization problems, ranging from optics, to signal processing, to radar and acoustics, involve constraints on the Fourier transform of a function. It is well-known that the {\em fast Fourier…

Optimization and Control · Mathematics 2012-09-05 Robert J. Vanderbei

Matrix factorization (MF) has become a common approach to collaborative filtering, due to ease of implementation and scalability to large data sets. Two existing drawbacks of the basic model is that it does not incorporate side information…

Machine Learning · Statistics 2014-07-30 Cody Severinski , Ruslan Salakhutdinov

In this paper, an integral identity for twice differentiable functions is generalized. Then, by using convexity of |f''| or q-th power of |f''| and with the aid of power mean and Holder's inequalities we achieved some new results. We also…

Functional Analysis · Mathematics 2015-03-10 Mustafa Gurbuz , Abdullah Yaradilmis