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06/10/2023
Optimized Gradient Tracking for Decentralized Online Learning
This work considers the problem of decentralized online learning, where ...
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05/26/2023
Sharpened Lazy Incremental Quasi-Newton Method
We consider the finite sum minimization of n strongly convex and smooth ...
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05/03/2023
Low-complexity subspace-descent over symmetric positive definite manifold
This work puts forth low-complexity Riemannian subspace descent algorith...
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06/17/2022
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning
Newton-type methods are popular in federated learning due to their fast ...
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10/22/2021
Projection-Free Algorithm for Stochastic Bi-level Optimization
This work presents the first projection-free algorithm to solve stochast...
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07/14/2021
Zeroth and First Order Stochastic Frank-Wolfe Algorithms for Constrained Optimization
This paper considers stochastic convex optimization problems with two se...
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06/19/2021
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
Federated Learning (FL) refers to the paradigm where multiple worker nod...
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02/03/2021
Optimizing QoS for Erasure-Coded Wireless Data Centers
Cloud computing facilitates the access of applications and data from any...
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12/17/2020
Stochastic Compositional Gradient Descent under Compositional constraints
This work studies constrained stochastic optimization problems where the...
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12/08/2020
A Primal-Dual Framework for Decentralized Stochastic Optimization
We consider the decentralized convex optimization problem, where multipl...
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11/13/2020
Sparse Representations of Positive Functions via Projected Pseudo-Mirror Descent
We consider the problem of expected risk minimization when the populatio...
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10/03/2020
Practical Precoding via Asynchronous Stochastic Successive Convex Approximation
We consider stochastic optimization of a smooth non-convex loss function...
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08/13/2020
Conservative Stochastic Optimization with Expectation Constraints
This paper considers stochastic convex optimization problems where the o...
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05/25/2020
Dynamic Cache Management In Content Delivery Networks
The importance of content delivery networks (CDN) continues to rise with...
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05/01/2020
Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction
In this work, we propose a distributed algorithm for stochastic non-conv...
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04/23/2020
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck
Gaussian processes provide a framework for nonlinear nonparametric Bayes...
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01/06/2020
A Generalized Framework for Autonomous Calibration of Wheeled Mobile Robots
Robotic calibration allows for the fusion of data from multiple sensors ...
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12/12/2019
Parallel Restarted SPIDER – Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity
In this paper, we propose a distributed algorithm for stochastic smooth,...
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10/25/2019
Model Free Calibration of Wheeled Robots Using Gaussian Process
Robotic calibration allows for the fusion of data from multiple sensors ...
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09/25/2019
Optimally Compressed Nonparametric Online Learning
Batch training of machine learning models based on neural networks is no...
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09/12/2019
Nonstationary Nonparametric Online Learning: Balancing Dynamic Regret and Model Parsimony
An open challenge in supervised learning is conceptual drift: a data poi...
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08/01/2019
Adaptive Kernel Learning in Heterogeneous Networks
We consider the framework of learning over decentralized networks, where...
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07/21/2019
Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I
In this two-part work, we propose an algorithmic framework for solving n...
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07/20/2019
Optimal Design of Queuing Systems via Compositional Stochastic Programming
Well-designed queuing systems form the backbone of modern communications...
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05/16/2019
Online Learning over Dynamic Graphs via Distributed Proximal Gradient Algorithm
We consider the problem of tracking the minimum of a time-varying convex...
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10/18/2018
On Socially Optimal Traffic Flow in the Presence of Random Users
Traffic assignment is an integral part of urban city planning. Roads and...
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10/08/2018
Decentralized Multi-Antenna Coded Caching with Cyclic Exchanges
This paper considers a single cell multi-antenna base station delivering...
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12/21/2016
Stochastic Multidimensional Scaling
Multidimensional scaling (MDS) is a popular dimensionality reduction tec...
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11/29/2012