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In this paper, we propose an efficient approach for the compression and representation of volumetric data utilizing coordinate-based networks and multi-resolution hash encoding. Efficient compression of volumetric data is crucial for…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Sudarshan Devkota , Sumanta Pattanaik

We perform an extended numerical search for practical fermion-to-qubit encodings with error correcting properties. Ideally, encodings should strike a balance between a number of the seemingly incompatible attributes, such as having a high…

Quantum Physics · Physics 2024-05-29 Fedor Simkovic , Martin Leib , Francisco Revson F. Pereira

Providing security in the transmission of images and other multimedia data has become one of the most important scientific and practical issues. In this paper, a method for compressing and encryption images is proposed, which can safely…

Multimedia · Computer Science 2022-08-25 Mahdi Shariatzadeh , Mahdi Eftekhari , Mohammad Javad Rostami

Manifold embedding algorithms map high-dimensional data down to coordinates in a much lower-dimensional space. One of the aims of dimension reduction is to find intrinsic coordinates that describe the data manifold. The coordinates returned…

Machine Learning · Statistics 2021-07-30 Samson Koelle , Hanyu Zhang , Marina Meila , Yu-Chia Chen

High-energy, large-scale particle colliders in nuclear and high-energy physics generate data at extraordinary rates, reaching up to $1$ terabyte and several petabytes per second, respectively. The development of real-time, high-throughput…

Artificial Intelligence · Computer Science 2024-12-03 Xihaier Luo , Samuel Lurvey , Yi Huang , Yihui Ren , Jin Huang , Byung-Jun Yoon

Compressive imaging is an emerging application of compressed sensing, devoted to acquisition, encoding and reconstruction of images using random projections as measurements. In this paper we propose a novel method to provide a scalable…

Information Theory · Computer Science 2013-10-07 Diego Valsesia , Enrico Magli

A spread code is a set of vector spaces of a fixed dimension over a finite field Fq with certain properties used for random network coding. It can be constructed in different ways which lead to different decoding algorithms. In this work we…

Information Theory · Computer Science 2014-06-20 Felice Manganiello , Anna-Lena Trautmann

As compared to a large spectrum of performance optimizations, relatively little effort has been dedicated to optimize other aspects of embedded applications such as memory space requirements, power, real-time predictability, and…

Other Computer Science · Computer Science 2011-11-09 O. Ozturk , H. Saputra , M. Kandemir , I. Kolcu

Due to the substantial scale of Large Language Models (LLMs), the direct application of conventional compression methodologies proves impractical. The computational demands associated with even minimal gradient updates present challenges,…

Machine Learning · Computer Science 2023-12-13 Arnav Chavan , Nahush Lele , Deepak Gupta

Compressed inverted indices in use today are based on the idea of gap compression: documents pointers are stored in increasing order, and the gaps between successive document pointers are stored using suitable codes which represent smaller…

Information Retrieval · Computer Science 2012-06-20 Sebastiano Vigna

Pixel antenna is a promising antenna technology that enables flexible adjustment of radiation characteristics and enhancement of wireless systems through antenna coding. This work proposes a novel deep learning-based antenna coding…

Information Theory · Computer Science 2026-03-02 Binzhou Zuo , Shanpu Shen , Hongyu Li

We design a heuristic method, a genetic algorithm, for the computation of an upper bound of the minimum distance of a linear code over a finite field. By the use of the row reduced echelon form, we obtain a permutation encoding of the…

Information Theory · Computer Science 2018-07-20 José Gómez-Torrecillas , F. J. Lobillo , Gabriel Navarro

We develop a new approach for distributed distance computation in planar graphs that is based on a variant of the metric compression problem recently introduced by Abboud et al. [SODA'18]. One of our key technical contributions is in…

Data Structures and Algorithms · Computer Science 2019-12-30 Jason Li , Merav Parter

We design quantum compression algorithms for parametric families of tensor network states. We first establish an upper bound on the amount of memory needed to store an arbitrary state from a given state family. The bound is determined by…

Quantum Physics · Physics 2021-09-28 Ge Bai , Yuxiang Yang , Giulio Chiribella

An effective method for compression of ECG signals, which falls within the transform lossy compression category, is proposed. The transformation is realized by a fast wavelet transform. The effectiveness of the approach, in relation to the…

Signal Processing · Electrical Eng. & Systems 2019-01-03 Laura Rebollo-Neira

In this paper we propose a novel approach to model compression termed Architecture Compression. Instead of operating on the weight or filter space of the network like classical model compression methods, our approach operates on the…

Computer Vision and Pattern Recognition · Computer Science 2019-03-13 Anubhav Ashok

Nowadays, the digital world is most focused on storage space and speed. With the growing demand for better bandwidth utilization, efficient image data compression techniques have emerged as an important factor for image data transmission…

Information Theory · Computer Science 2012-09-26 Rehna. V. J , Jeyakumar. M. K

We revisit a standard polygon containment problem: given a convex $k$-gon $P$ and a convex $n$-gon $Q$ in the plane, find a placement of $P$ inside $Q$ under translation and rotation (if it exists), or more generally, find the largest copy…

Computational Geometry · Computer Science 2024-03-21 Timothy M. Chan , Isaac M. Hair

Constrained coding plays a key role in optimizing performance and mitigating errors in applications such as storage and communication, where specific constraints on codewords are required. While non-parametric constraints have been…

Information Theory · Computer Science 2025-05-05 Daniella Bar-Lev , Michael Shlizerman

Neural-based image and video codecs are significantly more power-efficient when weights and activations are quantized to low-precision integers. While there are general-purpose techniques for reducing quantization effects, large losses can…

Image and Video Processing · Electrical Eng. & Systems 2023-01-26 Amir Said , Reza Pourreza , Hoang Le