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Perhaps the most straightforward classifier in the arsenal or machine learning techniques is the Nearest Neighbour Classifier -- classification is achieved by identifying the nearest neighbours to a query example and using those neighbours…

Machine Learning · Computer Science 2021-08-10 Padraig Cunningham , Sarah Jane Delany

The competitive Coding approach (CompCode) is one of the most promising methods for palmprint recognition. Due to its high performance and simple formulation, it has been continuously studied for many years. However, although numerous…

Computer Vision and Pattern Recognition · Computer Science 2022-07-01 Lingfei Song , Hua Huang

We consider the scenario of broadcasting for real-time applications and loss recovery via instantly decodable network coding. Past work focused on minimizing the completion delay, which is not the right objective for real-time applications…

Networking and Internet Architecture · Computer Science 2014-05-14 Anh Le , Arash S. Tehrani , Alexandros G. Dimakis , Athina Markopoulou

Quantum error correction, which utilizes logical qubits that are encoded as redundant multiple physical qubits to find and correct errors in physical qubits, is indispensable for practical quantum computing. Surface code is considered to be…

Machine Learning · Computer Science 2025-09-15 Hoshitaro Ohnishi , Hideo Mukai

We consider a wireless sensors network scenario where two nodes detect correlated sources and deliver them to a central collector via a wireless link. Differently from the Slepian-Wolf approach to distributed source coding, in the proposed…

Information Theory · Computer Science 2007-07-13 A. Abrardo

The strongly correlated systems we use to realise quantum error-correcting codes may give rise to high-weight, problematic errors. Encouragingly, we can expect local quantum error-correcting codes with no string-like logical operators $-$…

Quantum Physics · Physics 2021-07-14 Georgia M. Nixon , Benjamin J. Brown

The bee-identification problem, formally defined by Tandon, Tan and Varshney (2019), requires the receiver to identify "bees" using a set of unordered noisy measurements. In this previous work, Tandon, Tan, and Varshney studied error…

Information Theory · Computer Science 2022-12-21 Han Mao Kiah , Alexander Vardy , Hanwen Yao

Neural network-based decoding methods show promise in enhancing error correction performance but face challenges with punctured codes. In particular, existing methods struggle to adapt to variable code rates or meet protocol compatibility…

Machine Learning · Computer Science 2025-10-31 Yongli Yan , Linglong Dai

In this paper, we propose a policy-guided Monte Carlo Tree Search (MCTS) decoder that achieves near maximum-likelihood decoding (MLD) performance for short block codes. The MCTS decoder searches for test error patterns (TEPs) in the…

Information Theory · Computer Science 2025-11-13 Y. Tian , C. Yue , P. Cheng , G. Pang , B. Vucetic , Y. Li

Quantum low-density parity-check codes are a promising candidate for fault-tolerant quantum computing with considerably reduced overhead compared to the surface code. However, the lack of a practical decoding algorithm remains a barrier to…

This work presents two new construction techniques for q-ary Gossip codes from tdesigns and Traceability schemes. These Gossip codes achieve the shortest code length specified in terms of code parameters and can withstand erasures in…

Cryptography and Security · Computer Science 2007-05-23 Ravi S. Veerubhotla , Ashutosh Saxena , V. P. Gulati , A. K. Pujari

Transformer-based NLP models are powerful but have high computational costs that limit deployment. Finetuned encoder-decoder models are popular in specialized domains and can outperform larger more generalized decoder-only models, such as…

Computation and Language · Computer Science 2024-11-19 Bo-Ru Lu , Nikita Haduong , Chien-Yu Lin , Hao Cheng , Noah A. Smith , Mari Ostendorf

Background Nucleotide sequences contain multiple codes responsible for organism's functioning and structure. They can be investigated by various signal processing methods. These techniques are well suited for indication of frequently…

Quantitative Methods · Quantitative Biology 2007-05-23 Simon Kogan

In its most elementary form, compressed sensing studies the design of decoding algorithms to recover a sufficiently sparse vector or code from a lower dimensional linear measurement vector. Typically it is assumed that the decoder has…

Machine Learning · Computer Science 2021-07-20 Michael Murray , Jared Tanner

It has been widely observed that there exists a fundamental trade-off between the minimum (Hamming) distance properties and the iterative decoding convergence behavior of turbo-like codes. While capacity achieving code ensembles typically…

An anytime decoding algorithm for tree codes using Monte-Carlo tree search is proposed. The meaning of anytime decoding here is twofold: 1) the decoding algorithm is an anytime algorithm, whose decoding performance improves as more…

Information Theory · Computer Science 2021-05-04 Aolin Xu

This paper proposes a polar code construction scheme that reduces constituent-code supplemented decoding latency. Constituent codes are the sub-codewords with specific patterns. They are used to accelerate the successive cancellation…

Information Theory · Computer Science 2017-09-22 Tiben Che , Gwan Choi

Network coding is known as a promising approach to improve wireless network performance. How to discover the coding opportunity in relay nodes is really important for it. There are more coding chances, there are more times it can improve…

Networking and Internet Architecture · Computer Science 2012-05-30 Yunlong Zhao , Zhao Dong , Masayuki Iwai , Kaoru Sezaki , Yoshito Tobe

We present a two-step decoder for the parity code and evaluate its performance in code-capacity and faulty-measurement settings. For noiseless measurements, we find that the decoding problem can be reduced to a series of repetition codes…

We present the self-encoder, a neural network trained to guess the identity of each data sample. Despite its simplicity, it learns a very useful representation of data, in a self-supervised way. Specifically, the self-encoder learns to…

Machine Learning · Computer Science 2023-06-27 Armand Boschin , Thomas Bonald , Marc Jeanmougin
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