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Neural networks can efficiently encode the probability distribution of errors in an error correcting code. Moreover, these distributions can be conditioned on the syndromes of the corresponding errors. This paves a path forward for a…

Quantum Physics · Physics 2017-09-12 Stefan Krastanov , Liang Jiang

In this paper, we study the problem of remote state estimation, in the presence of a passive eavesdropper. An authorized user estimates the state of an unstable linear plant, based on the packets received from a sensor, while the packets…

Systems and Control · Computer Science 2017-09-15 Anastasios Tsiamis , Konstantinos Gatsis , George J. Pappas

Network coding is a highly efficient data dissemination mechanism for wireless networks. Since network coded information can only be recovered after delivering a sufficient number of coded packets, the resulting decoding delay can become…

Information Theory · Computer Science 2016-11-17 Rui A. Costa , Daniele Munaretto , Joerg Widmer , Joao Barros

In this paper, we introduce TreeCoders, a novel family of transformer trees. We moved away from traditional linear transformers to complete k-ary trees. Transformer blocks serve as nodes, and generic classifiers learn to select the best…

Computation and Language · Computer Science 2024-11-12 Pierre Colonna D'Istria , Abdulrahman Altahhan

Real-time applications require latencies on the order of a millisecond with very high reliabilities, paralleling the requirements for high-performance industrial control. Current wireless technologies like WiFi, Bluetooth, LTE, etc. are…

Information Theory · Computer Science 2018-03-15 Vasuki Narasimha Swamy , Paul Rigge , Gireeja Ranade , Anant Sahai , Borivoje Nikolic

We examine the issue of separation and code design for networks that operate over finite fields. We demonstrate that source-channel (or source-network) separation holds for several canonical network examples like the noisy multiple access…

Information Theory · Computer Science 2007-07-13 Siddharth Ray , Michelle Effros , Muriel Medard , Ralf Koetter , Tracey Ho , David Karger , Jinane Abounadi

Speculative decoding is a technique to leverage hardware concurrency in order to enable multiple steps of token generation in a single forward pass, thus improving the efficiency of large-scale autoregressive (AR) Transformer models.…

Machine Learning · Computer Science 2025-10-29 Yangchao Wu , Zongyue Qin , Alex Wong , Stefano Soatto

Self-adaptive software is considered as the most advanced approach and its development attracts a lot of attention. Decentralization is an effective way to design and manage the complexity of modern self-adaptive software systems. However,…

Software Engineering · Computer Science 2018-01-01 Nianyu Li , Di Bai , Zhuoqun Yang , Wenpin Jiao

Hierarchical tree structures are common in many real-world systems, from tree roots and branches to neuronal dendrites and biologically inspired artificial neural networks, as well as in technological networks for organizing and searching…

Statistical Mechanics · Physics 2025-02-04 Davide Cipollini , Lambert Schomaker

In practice, LDPC codes are decoded using message passing methods. These methods offer good performance but tend to converge slowly and sometimes fail to converge and to decode the desired codewords correctly. Recently, tree-reweighted…

Information Theory · Computer Science 2014-03-05 J. Li , R. C. de Lamare , H. Wymeersch

Tree codes, introduced by Schulman, are combinatorial structures essential to coding for interactive communication. An infinite family of tree codes with both rate and distance bounded by positive constants is called asymptotically good.…

Information Theory · Computer Science 2019-09-18 Anand Kumar Narayanan , Matthew Weidner

Guessing Random Additive Noise Decoding (GRAND) and its variants, known for their near-maximum likelihood performance, have been introduced in recent years. One such variant, Segmented GRAND, reduces decoding complexity by generating only…

Information Theory · Computer Science 2025-12-19 Lukas Rapp , Jiewei Feng , Muriel Médard , Ken R. Duffy

Hinging on ideas from physical-layer network coding, some promising proposals of coded random access systems seek to improve system performance (while preserving low complexity) by means of packet repetitions and decoding of linear…

Information Theory · Computer Science 2018-05-30 Adriano Pastore , Paul de Kerret , Monica Navarro , David Gregoratti , David Gesbert

Network coding is famous for significantly improving the throughput of networks. The successful decoding of the network coded data relies on some side information of the original data. In that framework, independent data flows are usually…

Networking and Internet Architecture · Computer Science 2015-05-22 Zhengchuan Chen , Ke Xiong , Pingyi Fan , Chen Chen

A networked controlled system (NCS) in which the plant communicates to the controller over a channel with random delay loss is considered. The channel model is motivated by recent development of tree codes for NCS, which effectively…

Systems and Control · Computer Science 2016-07-28 Mohammad Kazem Izadinasab , Amir Homayoun Bahari Sani , Farshad Lahouti , Babak Hassibi

The design of codes for feedback-enabled communications has been a long-standing open problem. Recent research on non-linear, deep learning-based coding schemes have demonstrated significant improvements in communication reliability over…

Information Theory · Computer Science 2023-06-09 Junghoon Kim , Taejoon Kim , David Love , Christopher Brinton

Departing from traditional communication theory where decoding algorithms are assumed to perform without error, a system where noise perturbs both computational devices and communication channels is considered here. This paper studies…

Information Theory · Computer Science 2010-05-31 Lav R. Varshney

We consider the question of interactive communication, in which two remote parties perform a computation while their communication channel is (adversarially) noisy. We extend here the discussion into a more general and stronger class of…

Data Structures and Algorithms · Computer Science 2016-05-25 Mark Braverman , Ran Gelles , Jieming Mao , Rafail Ostrovsky

We investigate an application in the automatic tuning of computer codes, an area of research that has come to prominence alongside the recent rise of distributed scientific processing and heterogeneity in high-performance computing…

Applications · Statistics 2013-04-17 Robert B. Gramacy , Matt Taddy , Stefan M. Wild

Owing to their inherently interpretable structure, decision trees are commonly used in applications where interpretability is essential. Recent work has focused on improving various aspects of decision trees, including their predictive…

Machine Learning · Statistics 2023-05-30 Dimitris Bertsimas , Vassilis Digalakis