121 citations · 413 across the 32 of their papers we have counts for
13 papers · 1 filter
Sparse Regression Codes
Ramji Venkataramanan, Sekhar Tatikonda, Andrew Barron
Developing computationally-efficient codes that approach the Shannon-theoretic limits for communication and compression has long been one of the major goals of information and codi…
The Rate-Distortion Function and Excess-Distortion Exponent of Sparse Regression Codes with Optimal Encoding
Ramji Venkataramanan, Sekhar Tatikonda
This paper studies the performance of sparse regression codes for lossy compression with the squared-error distortion criterion. In a sparse regression code, codewords are linear c…
Sparse Regression Codes for Multi-terminal Source and Channel Coding
Ramji Venkataramanan, Sekhar Tatikonda
We study a new class of codes for Gaussian multi-terminal source and channel coding. These codes are designed using the statistical framework of high-dimensional linear regression…
Message-Passing Algorithms for Quadratic Minimization
Nicholas Ruozzi, Sekhar Tatikonda
Gaussian belief propagation (GaBP) is an iterative algorithm for computing the mean of a multivariate Gaussian distribution, or equivalently, the minimum of a multivariate positive…
Lossy Compression via Sparse Linear Regression: Computationally Efficient Encoding and Decoding
Ramji Venkataramanan, Tuhin Sarkar, Sekhar Tatikonda
We propose computationally efficient encoders and decoders for lossy compression using a Sparse Regression Code. The codebook is defined by a design matrix and codewords are struct…
Rewritable storage channels with hidden state
Ramji Venkataramanan, Sekhar Tatikonda, Luis Lastras +1
Many storage channels admit reading and rewriting of the content at a given cost. We consider rewritable channels with a hidden state which models the unknown characteristics of th…
Lossy Compression via Sparse Linear Regression: Performance under Minimum-distance Encoding
Ramji Venkataramanan, Antony Joseph, Sekhar Tatikonda
We study a new class of codes for lossy compression with the squared-error distortion criterion, designed using the statistical framework of high-dimensional linear regression. Cod…
Achievable Rates for Channels with Deletions and Insertions
Ramji Venkataramanan, Sekhar Tatikonda, Kannan Ramchandran
This paper considers a binary channel with deletions and insertions, where each input bit is transformed in one of the following ways: it is deleted with probability d, or an extra…
Message-Passing Algorithms: Reparameterizations and Splittings
Nicholas Ruozzi, Sekhar Tatikonda
The max-product algorithm, a local message-passing scheme that attempts to compute the most probable assignment (MAP) of a given probability distribution, has been successfully emp…
Opportunistic capacity and error exponent regions for compound channel with feedback
Aditya Mahajan, Sekhar Tatikonda
Variable length communication over a compound channel with feedback is considered. Traditionally, capacity of a compound channel without feedback is defined as the maximum rate tha…
Capacity-achieving Feedback Scheme for Gaussian Finite-State Markov Channels with Channel State Information
Jialing Liu, Nicola Elia, Sekhar Tatikonda
In this paper, we propose capacity-achieving communication schemes for Gaussian finite-state Markov channels (FSMCs) subject to an average channel input power constraint, under the…
On the error exponent of variable-length block-coding schemes over finite-state Markov channels with feedback
Giacomo Como, Serdar Yuksel, Sekhar Tatikonda
The error exponent of Markov channels with feedback is studied in the variable-length block-coding setting. Burnashev's classic result is extended and a single letter characterizat…
The Capacity of Channels with Feedback
Sekhar Tatikonda, Sanjoy Mitter
We introduce a general framework for treating channels with memory and feedback. First, we generalize Massey's concept of directed information and use it to characterize the feedba…