
A Guide to Reproducible Research in Signal Processing and Machine Learning
Reproducibility is a growing problem that has been extensively studied a...
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FASTPCA: A Fast and Exact Algorithm for Distributed Principal Component Analysis
Principal Component Analysis (PCA) is a fundamental data preprocessing t...
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A hybrid modelbased and learningbased approach for classification using limited number of training samples
The fundamental task of classification given a limited number of trainin...
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A Minimax Lower Bound for LowRank MatrixVariate Logistic Regression
This paper considers the problem of matrixvariate logistic regression. ...
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Distributed Principal Subspace Analysis for Partitioned Big Data: Algorithms, Analysis, and Implementation
Principal Subspace Analysis (PSA) is one of the most popular approaches ...
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Boundary Conditions for Linear Exit Time Gradient Trajectories Around Saddle Points: Analysis and Algorithm
Gradientrelated firstorder methods have become the workhorse of large...
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A Linearly Convergent Algorithm for Distributed Principal Component Analysis
Principal Component Analysis (PCA) is the workhorse tool for dimensional...
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Exit Time Analysis for Approximations of Gradient Descent Trajectories Around Saddle Points
This paper considers the problem of understanding the exit time for traj...
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Scalingup Distributed Processing of Data Streams for Machine Learning
Emerging applications of machine learning in numerous areas involve cont...
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Learning Product Graphs Underlying Smooth Graph Signals
Realworld data is often times associated with irregular structures that...
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Distributed Stochastic Algorithms for Highrate Streaming Principal Component Analysis
This paper considers the problem of estimating the principal eigenvector...
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Tensor Regression Using Lowrank and Sparse Tucker Decompositions
This paper studies a tensorstructured linear regression model with a sc...
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Adversaryresilient Inference and Machine Learning: From Distributed to Decentralized
While the last few decades have witnessed a huge body of work devoted to...
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BRIDGE: Byzantineresilient Decentralized Gradient Descent
Decentralized optimization techniques are increasingly being used to lea...
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LearningAided Physical Layer Attacks Against Multicarrier Communications in IoT
InternetofThings (IoT) devices that are limited in power and processin...
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Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms
This work addresses the problem of learning sparse representations of te...
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Identifiability of Kroneckerstructured Dictionaries for Tensor Data
This paper derives sufficient conditions for reliable recovery of coordi...
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STARK: Structured Dictionary Learning Through Rankone Tensor Recovery
In recent years, a class of dictionaries have been proposed for multidim...
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ByRDiE: Byzantineresilient distributed coordinate descent for decentralized learning
Distributed machine learning algorithms enable processing of datasets th...
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ExSIS: Extended Sure Independence Screening for Ultrahighdimensional Linear Models
Statistical inference can be computationally prohibitive in ultrahighdi...
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Stochastic Optimization from Distributed, Streaming Data in Ratelimited Networks
Motivated by machine learning applications in networks of sensors, inter...
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Human Action Attribute Learning From Video Data Using LowRank Representations
Representation of human actions as a sequence of human body movements or...
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Minimax Lower Bounds for KroneckerStructured Dictionary Learning
Dictionary learning is the problem of estimating the collection of atomi...
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Cloud KSVD: A Collaborative Dictionary Learning Algorithm for Big, Distributed Data
This paper studies the problem of dataadaptive representations for big,...
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Learning the nonlinear geometry of highdimensional data: Models and algorithms
Modern information processing relies on the axiom that highdimensional ...
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Group Model Selection Using Marginal Correlations: The Good, the Bad and the Ugly
Group model selection is the problem of determining a small subset of gr...
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Waheed U. Bajwa
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Associate Professor of Electrical and Computer Engineering at Rutgers University since 2017, Chief Data Consultant at DealSmash since 2016, Associate Editor at IEEE Signal Processing Letters from 20142017, Assistant Professor at Rutgers University from 20112017