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eXmY is a novel data type for quantization of ML models. It supports both arbitrary bit widths and arbitrary integer and floating point formats. For example, it seamlessly supports 3, 5, 6, 7, 9 bit formats. For a specific bit width, say 7,…

Machine Learning · Computer Science 2024-05-27 Aditya Agrawal , Matthew Hedlund , Blake Hechtman

The cluster-weighted model (CWM) is a mixture model with random covariates which allows for flexible clustering and density estimation of a random vector composed by a response variable and by a set of covariates. In this class of models,…

Methodology · Statistics 2013-08-06 Salvatore Ingrassia , Antonio Punzo

Recently, linear codes with few weights have been constructed and extensively studied. In this paper, for an odd prime p, we determined the complete weight enumerator of two classes of p-ary linear codes constructed from defining set.…

Information Theory · Computer Science 2015-12-24 Qiuyan Wang , Fei Li , Kelan Ding , Dongdai Lin

Analog error correction codes have been proposed for analog in-memory computing on resistive crossbars, which can accelerate vector-matrix multiplication for machine learning. Unlike traditional communication or storage channels, this…

Information Theory · Computer Science 2026-05-29 Ziyuan Zhu , Changcheng Yuan , Ron M. Roth , Paul H. Siegel , Anxiao Jiang

As quantum computing moves toward fault-tolerant architectures, quantum error correction (QEC) decoder performance is increasingly critical for scalability. Understanding the impact of transitioning from floating-point software to…

Quantum Physics · Physics 2026-04-22 Francisco Garcia-Herrero , Javier Valls , Llanos Vergara-Picazo , Vicente Torres

Ensemble methods in machine learning aim to improve prediction accuracy by combining multiple models. This is achieved by ensuring diversity among predictors to capture different data aspects. Homogeneous ensembles use identical models,…

Quantum Physics · Physics 2025-11-04 Emiliano Tolotti , Enrico Blanzieri , Davide Pastorello

The large memory requirements of deep neural networks limit their deployment and adoption on many devices. Model compression methods effectively reduce the memory requirements of these models, usually through applying transformations such…

Machine Learning · Computer Science 2017-11-15 Brandon Reagen , Udit Gupta , Robert Adolf , Michael M. Mitzenmacher , Alexander M. Rush , Gu-Yeon Wei , David Brooks

We study error-correcting codes for permutations under the infinity norm, motivated by a novel storage scheme for flash memories call rank modulation. In this scheme, a set of $n$ flash cells are combined to create a single virtual…

Information Theory · Computer Science 2009-08-02 Itzhak Tamo , Moshe Schwartz

Reed-Muller codes encode an $m$-variate polynomial of degree $r$ by evaluating it on all points in $\{0,1\}^m$. We denote this code by $RM(m,r)$. The minimal distance of $RM(m,r)$ is $2^{m-r}$ and so it cannot correct more than half that…

Information Theory · Computer Science 2015-08-28 Ramprasad Saptharishi , Amir Shpilka , Ben Lee Volk

In this paper we introduce a new class of codes for over-loaded synchronous wireless CDMA systems which increases the number of users for a fixed number of chips without introducing any errors. In addition these codes support active user…

Information Theory · Computer Science 2008-10-07 Pedram Pad , Mahdi Soltanolkotabi , Saeed Hadikhanlou , Arash Enayati , Farokh Marvasti

Recently, linear codes constructed from defining sets have been investigated extensively and they have many applications. In this paper, for an odd prime $p$, we propose a class of $p$-ary linear codes by choosing a proper defining set.…

Information Theory · Computer Science 2017-07-07 Shudi Yang , Zheng-An Yao , Chang-An Zhao

Many hashing algorithms including minwise hashing (MinHash), one permutation hashing (OPH), and consistent weighted sampling (CWS) generate integers of $B$ bits. With $k$ hashes for each data vector, the storage would be $B\times k$ bits;…

Machine Learning · Computer Science 2023-06-29 Ping Li , Weijie Zhao

Quantum error correction is expected to be essential in large-scale quantum technologies. However, the substantial overhead of qubits it requires is thought to greatly limit its utility in smaller, near-term devices. Here we introduce a new…

Quantum Physics · Physics 2020-01-20 David Layden , Mo Chen , Paola Cappellaro

This paper computationally obtains optimal bounded-weight, binary, error-correcting codes for a variety of distance bounds and dimensions. We compare the sizes of our codes to the sizes of optimal constant-weight, binary, error-correcting…

Information Theory · Computer Science 2007-10-15 Russell Bent , Michael Schear , Lane A. Hemaspaandra , Gabriel Istrate

This paper studies random-coding error exponents of randomised list decoding, in which the decoder randomly selects $L$ messages with probabilities proportional to the decoding metric of the codewords. The exponents (or bounds) are given…

Information Theory · Computer Science 2026-01-15 Henrique K. Miyamoto , Sheng Yang

Quantum low density parity check (qLDPC) codes, particularly bivariate bicycle (BB) codes, achieve competitive fault tolerance thresholds while offering substantially higher encoding rates than planar surface codes. However, their…

Quantum Physics · Physics 2026-05-07 Nitish Kumar Chandra , Eneet Kaur , Reza Nejabati , Kaushik P. Seshadreesan

The weight distribution of error correction codes is a critical determinant of their error-correcting performance, making enumeration of utmost importance. In the case of polar codes, the minimum weight $\wm$ (which is equal to minimum…

Information Theory · Computer Science 2023-05-05 Mohammad Rowshan , Vlad-Florin Drăgoi , Jinhong Yuan

The determination of the weight distribution of linear codes has been a fascinating problem since the very beginning of coding theory. There has been a lot of research on weight enumerators of special cases, such as self-dual codes and…

Combinatorics · Mathematics 2021-09-28 Alessio Meneghetti , Marco Pellegrini , Massimiliano Sala

Bitwise operations are an important component of modern day programming. Many widely-used data structures (e.g., bitmap indices in databases) rely on fast bitwise operations on large bit vectors to achieve high performance. Unfortunately,…

We develop a new intermediate weak memory model, IMM, as a way of modularizing the proofs of correctness of compilation from concurrent programming languages with weak memory consistency semantics to mainstream multi-core architectures,…

Programming Languages · Computer Science 2018-11-12 Anton Podkopaev , Ori Lahav , Viktor Vafeiadis