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Explicit characterization of the capacity region of communication networks is a long standing problem. While it is known that network coding can outperform routing and replication, the set of feasible rates is not known in general.…

Information Theory · Computer Science 2016-04-13 Satyajit Thakor , Alex Grant , Terence Chan

The expressiveness of deep neural network (DNN) is a perspective to understandthe surprising performance of DNN. The number of linear regions, i.e. pieces thata piece-wise-linear function represented by a DNN, is generally used to…

Machine Learning · Computer Science 2020-12-09 Yutong Xie , Gaoxiang Chen , Quanzheng Li

This work investigates the fundamental limits of communication over a noisy discrete memoryless channel that wears out, in the sense of signal-dependent catastrophic failure. In particular, we consider a channel that starts as a memoryless…

Information Theory · Computer Science 2018-08-07 Ting-Yi Wu , Lav R. Varshney , Vincent Y. F. Tan

One of the paramount advantages of multi-level cache-enabled (MLCE) networks is pushing contents proximity to the network edge and proactively caching them at multiple transmitters (i.e., small base-stations (SBSs), unmanned aerial vehicles…

Information Theory · Computer Science 2021-02-09 Mohammed S. Al-Abiad , Md. Zoheb Hassan , Md. Jahangir Hossain

In this paper, we study a wireless packet broadcast system that uses linear network coding (LNC) to help receivers recover data packets that are missing due to packet erasures. We study two intertwined performance metrics, namely throughput…

Information Theory · Computer Science 2017-01-18 Mingchao Yu , Parastoo Sadeghi

Batched network coding is a variation of random linear network coding which has low computational and storage costs. In order to adapt to random fluctuations in the number of erasures in individual batches, it is not optimal to recode and…

Information Theory · Computer Science 2021-09-16 Hoover H. F. Yin , Bin Tang , Ka Hei Ng , Shenghao Yang , Xishi Wang , Qiaoqiao Zhou

Deployment of small cell base stations (SBSs) overlaying the coverage area of a macrocell BS (MBS) results in a two-tier hierarchical small cell network. Cross-tier and inter-tier interference not only jeopardize primary macrocell…

Information Theory · Computer Science 2016-12-20 Jiaheng Wang , Wei Guan , Yongming Huang , Robert Schober , Xiaohu You

The ability of overparameterized deep networks to generalize well has been linked to the fact that stochastic gradient descent (SGD) finds solutions that lie in flat, wide minima in the training loss -- minima where the output of the…

Machine Learning · Computer Science 2019-06-03 Vaishnavh Nagarajan , J. Zico Kolter

In this paper, wireless systems operating under queueing constraints in the form of limitations on the buffer violation probabilities are considered. The throughput under such constraints is captured by the effective capacity formulation.…

Information Theory · Computer Science 2010-09-16 Mustafa Cenk Gursoy

User cooperation based multi-hop wireless communication networks (MH-WCNs) as the key communication technological component of mobile social networks (MSNs) should be exploited to enhance the capability of accumulating data rates and…

Information Theory · Computer Science 2014-12-23 Mugen Peng , Qiang Hu , Xinqian Xie , Zhongyuan Zhao , H. Vincent Poor

We analyze a simple network where a source and a receiver are connected by a line of erasure channels of different reliabilities. Recent prior work has shown that random linear network coding can achieve the min-cut capacity and therefore…

Information Theory · Computer Science 2009-10-22 Theodoros K. Dikaliotis , Alexandros G. Dimakis , Tracey Ho , Michelle Effros

Recently, deep neural networks (DNNs) have been used extensively for automatic modulation classification (AMC), and the results have been quite promising. However, DNNs have high memory and computation requirements making them impractical…

Information Theory · Computer Science 2023-04-19 Deepsayan Sadhukhan , Nitin Priyadarshini Shankar , Nancy Nayak , Thulasi Tholeti , Sheetal Kalyani

We establish a margin based data dependent generalization error bound for a general family of deep neural networks in terms of the depth and width, as well as the Jacobian of the networks. Through introducing a new characterization of the…

Machine Learning · Computer Science 2019-07-05 Xingguo Li , Junwei Lu , Zhaoran Wang , Jarvis Haupt , Tuo Zhao

A multi-hop synchronous wirelss network is said to be unknown if the nodes have no knowledge of the topology. A basic task in wireless network is that of broadcasting a message (created by a fixed source node) to all nodes of the network.…

Data Structures and Algorithms · Computer Science 2007-05-23 Andrea E. F. Clementi , Angelo Monti , Riccardo Silvestri

In this work, minibatch MCMC sampling for feedforward neural networks is made more feasible. To this end, it is proposed to sample subgroups of parameters via a blocked Gibbs sampling scheme. By partitioning the parameter space, sampling is…

Machine Learning · Statistics 2023-07-25 Theodore Papamarkou

Binary-input memoryless channels with a runlength constrained input are considered. Upper bounds to the capacity of such noisy runlength constrained channels are derived using the dual capacity method with Markov test distributions…

Information Theory · Computer Science 2016-11-17 Andrew Thangaraj

A bound on the maximum information transmission rate through a cascade of Gaussian links is presented. The network model consists of a source node attempting to send a message drawn from a finite alphabet to a sink, through a cascade of…

Information Theory · Computer Science 2013-01-29 Ramanan Subramanian , Badri Vellambi , Ingmar Land

This work considers the smart repeater network where a single source $s$ wants to send two independent packet streams to destinations $\{d_1,d_2\}$ with the help of relay $r$. The transmission from $s$ or $r$ is modeled by packet erasure…

Information Theory · Computer Science 2016-05-05 Jaemin Han , Chih-Chun Wang

The paper introduces new bounds on the asymptotic density of parity-check matrices and the achievable rates under ML decoding of binary linear block codes transmitted over memoryless binary-input output-symmetric channels. The lower bounds…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

We discuss the problem of designing channel access architectures for enabling fast, low-latency, grant-free and uncoordinated uplink for densely packed wireless nodes. Specifically, we study random-access codes, previously introduced for…

Information Theory · Computer Science 2019-07-23 Suhas S Kowshik , Kirill Andreev , Alexey Frolov , Yury Polyanskiy