3 citations · 5 across the 13 of their papers we have counts for
15 papers
Consecutive Support Matching Induced Parameter Tuning Accelerates Momentum Iterative Hard Thresholding
Samrat Mukhopadhyay, Debasmita Mukherjee
Momentum-based acceleration of iterative hard thresholding (IHT) can dramatically speed up sparse signal recovery from linear measurements, but its effectiveness hinges on careful…
Online Learning for Approximately-Convex Functions with Long-term Adversarial Constraints
Dhruv Sarkar, Samrat Mukhopadhyay, Abhishek Sinha
We study an online learning problem with long-term budget constraints in the adversarial setting. In this problem, at each round , the learner selects an action from a convex de…
Follow The Approximate Sparse Leader for No-Regret Online Sparse Linear Approximation
Samrat Mukhopadhyay, Debasmita Mukherjee
We consider the problem of \textit{online sparse linear approximation}, where one predicts the best sparse approximation of a sequence of measurements in terms of linear combinatio…
Multiple Choice Hard Thresholding Pursuit (MCHTP) for Simultaneous Sparse Recovery and Sparsity Order Estimation
Samrat Mukhopadhyay, Himanshu Bhusan Mishra
We address the problem of sparse recovery using greedy compressed sensing recovery algorithms, without explicit knowledge of the sparsity. Estimating the sparsity order is a crucia…
Online Subset Selection using -Core with no Augmented Regret
Sourav Sahoo, Siddhant Chaudhary, Samrat Mukhopadhyay +1
We revisit the classic problem of optimal subset selection in the online learning set-up. Assume that the set consists of distinct elements. On the th round, an advers…
Dynamic Sample Complexity for Exact Sparse Recovery using Sequential Iterative Hard Thresholding
Samrat Mukhopadhyay
In this paper we consider the problem of exact recovery of a fixed sparse vector with the measurement matrices sequentially arriving along with corresponding measurements. We propo…
Online Caching with Optimal Switching Regret
Samrat Mukhopadhyay, Abhishek Sinha
We consider the classical uncoded caching problem from an online learning point-of-view. A cache of limited storage capacity can hold files at a time from a large catalog. A us…
Sparse Recovery Analysis of Generalized -Minimization with Results for Sparsity Promoting Functions with Monotonic Elasticity
Samrat Mukhopadhyay
In this paper we theoretically study exact recovery of sparse vectors from compressed measurements by minimizing a general nonconvex function that can be decomposed into the sum of…
On the MMSE Estimation of Norm of a Gaussian Vector under Additive White Gaussian Noise with Randomly Missing Input Entries
Samrat Mukhopadhyay
This paper considers the task of estimating the norm of a -dimensional random Gaussian vector from noisy measurements taken after many of the entries of the vector are \em…
A Two Stage Generalized Block Orthogonal Matching Pursuit (TSGBOMP) Algorithm
Samrat Mukhopadhyay, Mrityunjoy Chakraborty
Recovery of an unknown sparse signal from a few of its projections is the key objective of compressed sensing. Often one comes across signals that are not ordinarily sparse but are…
Modified Hard Thresholding Pursuit with Regularization Assisted Support Identification
Samrat Mukhopadhyay, Mrityunjoy Chakraborty
Hard thresholding pursuit (HTP) is a recently proposed iterative sparse recovery algorithm which is a result of combination of a support selection step from iterated hard threshold…
Deterministic and Randomized Diffusion based Iterative Generalized Hard Thresholding (DiFIGHT) for Distributed Sparse Signal Recovery
Samrat Mukhopadhyay, Mrityunjoy Chakraborty
In this paper we propose a distributed iterated hard thresholding algorithm termed DiFIGHT over a network that is built on the diffusion mechanism and also propose a modification o…
Signal Recovery in Uncorrelated and Correlated Dictionaries Using Orthogonal Least Squares
Samrat Mukhopadhyay, Prateek Vashishtha and, Mrityunjoy Chakraborty
Though the method of least squares has been used for a long time in solving signal processing problems, in the recent field of sparse recovery from compressed measurements, this me…
Performance Analysis of Norm Constrained Recursive Least Squares Algorithm
Samrat Mukhopadhyay, Bijit Kumar Das, Mrityunjoy Chakraborty
Performance analysis of norm constrained Recursive least Squares (RLS) algorithm is attempted in this paper. Though the performance pretty attractive compared to its various…
A Modified Multiple OLS (mOLS) Algorithm for Signal Recovery in Compressive Sensing
Samrat Mukhopadhyay, Siddhartha Satpathi, Mrityunjoy Chakraborty
Orthogonal least square (OLS) is an important sparse signal recovery algorithm for compressive sensing, which enjoys superior probability of success over other well-known recovery…