Variable-Length Stop-Feedback Codes With Finite Optimal Decoding Times for BI-AWGN Channels
In this paper, we are interested in the performance of a variable-length stop-feedback (VLSF) code with $m$ optimal decoding times for the binary-input additive white Gaussian noise channel. We...
Feedback Capacity of MIMO Gaussian Channels
Finding a computable expression for the feedback capacity of channels with colored Gaussian, additive noise is a long standing open problem. In this paper, we solve this problem in the scenario...
Reducing the LQG Cost with Minimal Communication
We study the linear quadratic Gaussian (LQG) control problem, in which the controller's observation of the system state is such that a desired cost is unattainable. To achieve the desired LQG...
Feedback capacity of Gaussian channels with memory
We consider the feedback capacity of a MIMO channel whose channel output is given by a linear state-space model driven by the channel inputs and a Gaussian process. The generality of our...
How to Query An Oracle? Efficient Strategies to Label Data
We consider the basic problem of querying an expert oracle for labeling a dataset in machine learning. This is typically an expensive and time consuming process and therefore, we seek ways to do...
Gaussian Multiple and Random Access in the Finite Blocklength Regime
This paper presents finite-blocklength achievability bounds for the Gaussian multiple access channel (MAC) and random access channel (RAC) under average-error and maximal-power constraints. Using...
Variable-Length Sparse Feedback Codes for Point-to-Point, Multiple Access, and Random Access Channels
This paper investigates variable-length stop-feedback codes for memoryless channels in point-to-point, multiple access, and random access communication scenarios. The proposed codes employ $L$...
Instantaneous SED coding over a DMC
In this paper, we propose a novel code for transmitting a sequence of $n$ message bits in real time over a discrete-memoryless channel (DMC) with noiseless feedback, where the message bits stream...
Optimal Causal Rate-Constrained Sampling of the Wiener Process
We consider the following communication scenario. An encoder causally observes the Wiener process and decides when and what to transmit about it. A decoder makes real-time estimation of the...
Differentially Quantized Gradient Methods
Consider the following distributed optimization scenario. A worker has access to training data that it uses to compute the gradients while a server decides when to stop iterative computation based...
Lossless Source Coding in the Point-to-Point, Multiple Access, and Random Access Scenarios
This work studies point-to-point, multiple access, and random access lossless source coding in the finite-blocklength regime. In each scenario, a random coding technique is developed and used to...
Random Access Channel Coding in the Finite Blocklength Regime
Consider a random access communication scenario over a channel whose operation is defined for any number of possible transmitters. As in the model recently introduced by Polyanskiy for the...
A lower bound on the differential entropy of log-concave random vectors with applications
We derive a lower bound on the differential entropy of a log-concave random variable $X$ in terms of the $p$-th absolute moment of $X$. The new bound leads to a reverse entropy power inequality...
Optimal Causal Rate-Constrained Sampling for a Class of Continuous Markov Processes
Consider the following communication scenario. An encoder observes a stochastic process and causally decides when and what to transmit about it, under a constraint on the expected number of bits...
Two-layer Coded Channel Access with Collision Resolution: Design and Analysis
We propose a two-layer coding architecture for communication of multiple users over a shared slotted medium enabling joint collision resolution and decoding. Each user first encodes its...
The Dispersion of the Gauss-Markov Source
The Gauss-Markov source produces $U_i = aU_{i-1} + Z_i$ for $i\geq 1$, where $U_0 = 0$, $|a|<1$ and $Z_i\sim\mathcal{N}(0, \sigma^2)$ are i.i.d. Gaussian random variables. We consider lossy...
Nonstationary Gauss-Markov Processes: Parameter Estimation and Dispersion
This paper provides a precise error analysis for the maximum likelihood estimate $\hat{a}_{\text{ML}}(u_1^n)$ of the parameter $a$ given samples $u_1^n = (u_1, \ldots, u_n)'$ drawn from a...
The CEO problem with inter-block memory
An $n$-dimensional source with memory is observed by $K$ isolated encoders via parallel channels, who compress their observations to transmit to the decoder via noiseless rate-constrained links...