Shahin Shahrampour

research

∙ 02/23/2023

Dynamic Regret Analysis of Safe Distributed Online Optimization for Convex and Non-convex Problems

This paper addresses safe distributed online optimization over an unknow...

0 Ting-Jui Chang, et al. ∙

research

∙ 02/04/2023

TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Data

This work investigates the intersection of cross modal learning and semi...

0 Yinsong Wang, et al. ∙

research

∙ 09/25/2022

On the Stability Analysis of Open Federated Learning Systems

We consider the open federated learning (FL) systems, where clients may ...

10 Youbang Sun, et al. ∙

research

∙ 07/03/2022

Distributed Online System Identification for LTI Systems Using Reverse Experience Replay

Identification of linear time-invariant (LTI) systems plays an important...

0 Ting-Jui Chang, et al. ∙

research

∙ 03/15/2022

TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation

Real-time density estimation is ubiquitous in many applications, includi...

0 Yinsong Wang, et al. ∙

research

∙ 12/11/2021

A Sparse Expansion For Deep Gaussian Processes

Deep Gaussian Processes (DGP) enable a non-parametric approach to quanti...

0 Liang Ding, et al. ∙

research

∙ 05/29/2021

On Centralized and Distributed Mirror Descent: Exponential Convergence Analysis Using Quadratic Constraints

Mirror descent (MD) is a powerful first-order optimization technique tha...

0 Youbang Sun, et al. ∙

research

∙ 05/15/2021

Regret Analysis of Distributed Online LQR Control for Unknown LTI Systems

Online learning has recently opened avenues for rethinking classical opt...

0 Ting-Jui Chang, et al. ∙

research

∙ 02/14/2021

Decentralized Riemannian Gradient Descent on the Stiefel Manifold

We consider a distributed non-convex optimization where a network of age...

0 Shixiang Chen, et al. ∙

research

∙ 01/22/2021

On the Local Linear Rate of Consensus on the Stiefel Manifold

We study the convergence properties of Riemannian gradient method for so...

0 Shixiang Chen, et al. ∙

research

∙ 11/24/2020

Linear Convergence of Distributed Mirror Descent with Integral Feedback for Strongly Convex Problems

Distributed optimization often requires finding the minimum of a global ...

0 Youbang Sun, et al. ∙

research

∙ 09/29/2020

Distributed Online Linear Quadratic Control for Linear Time-invariant Systems

Classical linear quadratic (LQ) control centers around linear time-invar...

0 Ting-Jui Chang, et al. ∙

research

∙ 09/14/2020

Distributed Mirror Descent with Integral Feedback: Asymptotic Convergence Analysis of Continuous-time Dynamics

This work addresses distributed optimization, where a network of agents ...

0 Youbang Sun, et al. ∙

research

∙ 06/06/2020

Unconstrained Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems

The regret bound of dynamic online learning algorithms is often expresse...

0 Ting-Jui Chang, et al. ∙

research

∙ 06/05/2020

Learning from Non-IID Data in Hilbert Spaces: An Optimal Recovery Perspective

The notion of generalization in classical Statistical Learning is often ...

0 Simon Foucart, et al. ∙

research

∙ 06/05/2020

Overcoming the Curse of Dimensionality in Density Estimation with Mixed Sobolev GANs

We propose a novel GAN framework for non-parametric density estimation w...

0 Liang Ding, et al. ∙

research

∙ 04/28/2020

Distributed Projected Subgradient Method for Weakly Convex Optimization

The stochastic subgradient method is a widely-used algorithm for solving...

0 Shixiang Chen, et al. ∙

research

∙ 03/12/2020

Statistical and Topological Properties of Sliced Probability Divergences

The idea of slicing divergences has been proven to be successful when co...

0 Kimia Nadjahi, et al. ∙

research

∙ 02/28/2020

Generalized Sliced Distances for Probability Distributions

Probability metrics have become an indispensable part of modern statisti...

0 Soheil Kolouri, et al. ∙

research

∙ 02/12/2020

A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Space

In supervised learning using kernel methods, we encounter a large-scale ...

0 Shahin Shahrampour, et al. ∙

research

∙ 02/11/2020

Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features

Despite their success, kernel methods suffer from a massive computationa...

0 Liang Ding, et al. ∙

research

∙ 10/29/2019

Cell Association via Boundary Detection: A Scalable Approach Based on Data-Driven Random Features

The problem of cell association is considered for cellular users present...

0 Yinsong Wang, et al. ∙

research

∙ 10/11/2019

A General Scoring Rule for Randomized Kernel Approximation with Application to Canonical Correlation Analysis

Random features has been widely used for kernel approximation in large-s...

0 Yinsong Wang, et al. ∙

research

∙ 09/25/2019

A Mean-Field Theory for Kernel Alignment with Random Features in Generative Adversarial Networks

We propose a novel supervised learning method to optimize the kernel in ...

18 Masoud Badiei Khuzani, et al. ∙

research

∙ 09/20/2019

Distributed Parameter Estimation in Randomized One-hidden-layer Neural Networks

This paper addresses distributed parameter estimation in randomized one-...

0 Yinsong Wang, et al. ∙

research

∙ 03/20/2019

On Sampling Random Features From Empirical Leverage Scores: Implementation and Theoretical Guarantees

Random features provide a practical framework for large-scale kernel app...

0 Shahin Shahrampour, et al. ∙

research

∙ 10/09/2018

Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels

Nonlinear kernels can be approximated using finite-dimensional feature m...

0 Shahin Shahrampour, et al. ∙

research

∙ 12/19/2017

On Data-Dependent Random Features for Improved Generalization in Supervised Learning

The randomized-feature approach has been successfully employed in large-...

0 Shahin Shahrampour, et al. ∙

research

∙ 11/14/2017

On Optimal Generalizability in Parametric Learning

We consider the parametric learning problem, where the objective of the ...

0 Ahmad Beirami, et al. ∙

research

∙ 07/09/2017

Nonlinear Sequential Accepts and Rejects for Identification of Top Arms in Stochastic Bandits

We address the M-best-arm identification problem in multi-armed bandits....

0 Shahin Shahrampour, et al. ∙

research

∙ 02/21/2017

An Online Optimization Approach for Multi-Agent Tracking of Dynamic Parameters in the Presence of Adversarial Noise

This paper addresses tracking of a moving target in a multi-agent networ...

0 Shahin Shahrampour, et al. ∙

research

∙ 09/09/2016

Distributed Online Optimization in Dynamic Environments Using Mirror Descent

This work addresses decentralized online optimization in non-stationary ...

0 Shahin Shahrampour, et al. ∙

research

∙ 09/08/2016

On Sequential Elimination Algorithms for Best-Arm Identification in Multi-Armed Bandits

We consider the best-arm identification problem in multi-armed bandits, ...

0 Shahin Shahrampour, et al. ∙

research

∙ 09/14/2015

Learning without Recall by Random Walks on Directed Graphs

We consider a network of agents that aim to learn some unknown state of ...

0 Mohammad Amin Rahimian, et al. ∙

research

∙ 03/11/2015

Switching to Learn

A network of agents attempt to learn some unknown state of the world dra...

0 Shahin Shahrampour, et al. ∙

research

∙ 01/26/2015

Online Optimization : Competing with Dynamic Comparators

Recent literature on online learning has focused on developing adaptive ...

0 Ali Jadbabaie, et al. ∙

research

∙ 09/30/2014

Distributed Detection : Finite-time Analysis and Impact of Network Topology

This paper addresses the problem of distributed detection in multi-agent...

0 Shahin Shahrampour, et al. ∙

research

∙ 10/01/2013

Online Learning of Dynamic Parameters in Social Networks

This paper addresses the problem of online learning in a dynamic setting...

0 Shahin Shahrampour, et al. ∙

research

∙ 09/10/2013

Exponentially Fast Parameter Estimation in Networks Using Distributed Dual Averaging

In this paper we present an optimization-based view of distributed param...

0 Shahin Shahrampour, et al. ∙

Shahin Shahrampour

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