41 citations · 98 across the 12 of their papers we have counts for
15 papers
Data-Driven Low-Rank Neural Network Compression
Dimitris Papadimitriou, Swayambhoo Jain
Despite many modern applications of Deep Neural Networks (DNNs), the large number of parameters in the hidden layers makes them unattractive for deployment on devices with storage…
Efficacy of Bayesian Neural Networks in Active Learning
Vineeth Rakesh, Swayambhoo Jain
Obtaining labeled data for machine learning tasks can be prohibitively expensive. Active learning mitigates this issue by exploring the unlabeled data space and prioritizing the se…
Matrix Completion in the Unit Hypercube via Structured Matrix Factorization
Emanuele Bugliarello, Swayambhoo Jain, Vineeth Rakesh
Several complex tasks that arise in organizations can be simplified by mapping them into a matrix completion problem. In this paper, we address a key challenge faced by our company…
Minimum Uncertainty Based Detection of Adversaries in Deep Neural Networks
Fatemeh Sheikholeslami, Swayambhoo Jain, Georgios B. Giannakis
Despite their unprecedented performance in various domains, utilization of Deep Neural Networks (DNNs) in safety-critical environments is severely limited in the presence of even s…
Learning Generative Models of Structured Signals from Their Superposition Using GANs with Application to Denoising and Demixing
Mohammadreza Soltani, Swayambhoo Jain, Abhinav Sambasivan
Recently, Generative Adversarial Networks (GANs) have emerged as a popular alternative for modeling complex high dimensional distributions. Most of the existing works implicitly as…
Improved Support Recovery Guarantees for the Group Lasso With Applications to Structural Health Monitoring
Mojtaba Kadkhodaie Elyaderani, Swayambhoo Jain, Jeffrey Druce +2
This paper considers the problem of estimating an unknown high dimensional signal from noisy linear measurements, {when} the signal is assumed to possess a \emph{group-sparse} stru…
Noisy Tensor Completion for Tensors with a Sparse Canonical Polyadic Factor
Swayambhoo Jain, Alexander Gutierrez, Jarvis Haupt
In this paper we study the problem of noisy tensor completion for tensors that admit a canonical polyadic or CANDECOMP/PARAFAC (CP) decomposition with one of the factors being spar…
Block CUR: Decomposing Matrices using Groups of Columns
Urvashi Oswal, Swayambhoo Jain, Kevin S. Xu +1
A common problem in large-scale data analysis is to approximate a matrix using a combination of specifically sampled rows and columns, known as CUR decomposition. Unfortunately, in…
Rank-to-engage: New Listwise Approaches to Maximize Engagement
Swayambhoo Jain, Akshay Soni, Nikolay Laptev +1
For many internet businesses, presenting a given list of items in an order that maximizes a certain metric of interest (e.g., click-through-rate, average engagement time etc.) is c…
Noisy Inductive Matrix Completion Under Sparse Factor Models
Akshay Soni, Troy Chevalier, Swayambhoo Jain
Inductive Matrix Completion (IMC) is an important class of matrix completion problems that allows direct inclusion of available features to enhance estimation capabilities. These m…
A Compressed Sensing Based Decomposition of Electrodermal Activity Signals
Swayambhoo Jain, Urvashi Oswal, Kevin S. Xu +2
The measurement and analysis of Electrodermal Activity (EDA) offers applications in diverse areas ranging from market research, to seizure detection, to human stress analysis. Unfo…
On Convolutional Approximations to Linear Dimensionality Reduction Operators for Large Scale Data Processing
Swayambhoo Jain, Jarvis Haupt
In this paper, we examine the problem of approximating a general linear dimensionality reduction (LDR) operator, represented as a matrix with $m < n…
Noisy Matrix Completion under Sparse Factor Models
Akshay Soni, Swayambhoo Jain, Jarvis Haupt +1
This paper examines a general class of noisy matrix completion tasks where the goal is to estimate a matrix from observations obtained at a subset of its entries, each of which is…
Backhaul-Constrained Multi-Cell Cooperation Leveraging Sparsity and Spectral Clustering
Swayambhoo Jain, Seung-Jun Kim, Georgios B. Giannakis
Multi-cell cooperative processing with limited backhaul traffic is studied for cellular uplinks. Aiming at reduced backhaul overhead, a sparsity-regularized multi-cell receive-filt…
Compressive Measurement Designs for Estimating Structured Signals in Structured Clutter: A Bayesian Experimental Design Approach
Swayambhoo Jain, Akshay Soni, Jarvis Haupt
This work considers an estimation task in compressive sensing, where the goal is to estimate an unknown signal from compressive measurements that are corrupted by additive pre-meas…