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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...
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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...
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09/25/2022
On the Stability Analysis of Open Federated Learning Systems
We consider the open federated learning (FL) systems, where clients may ...
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07/03/2022
Distributed Online System Identification for LTI Systems Using Reverse Experience Replay
Identification of linear time-invariant (LTI) systems plays an important...
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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...
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12/11/2021
A Sparse Expansion For Deep Gaussian Processes
Deep Gaussian Processes (DGP) enable a non-parametric approach to quanti...
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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...
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05/15/2021
Regret Analysis of Distributed Online LQR Control for Unknown LTI Systems
Online learning has recently opened avenues for rethinking classical opt...
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02/14/2021
Decentralized Riemannian Gradient Descent on the Stiefel Manifold
We consider a distributed non-convex optimization where a network of age...
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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...
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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 ...
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09/29/2020
Distributed Online Linear Quadratic Control for Linear Time-invariant Systems
Classical linear quadratic (LQ) control centers around linear time-invar...
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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 ...
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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...
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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 ...
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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...
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04/28/2020
Distributed Projected Subgradient Method for Weakly Convex Optimization
The stochastic subgradient method is a widely-used algorithm for solving...
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03/12/2020
Statistical and Topological Properties of Sliced Probability Divergences
The idea of slicing divergences has been proven to be successful when co...
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02/28/2020
Generalized Sliced Distances for Probability Distributions
Probability metrics have become an indispensable part of modern statisti...
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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 ...
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02/11/2020
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features
Despite their success, kernel methods suffer from a massive computationa...
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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...
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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...
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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 ...
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09/20/2019
Distributed Parameter Estimation in Randomized One-hidden-layer Neural Networks
This paper addresses distributed parameter estimation in randomized one-...
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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...
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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...
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12/19/2017
On Data-Dependent Random Features for Improved Generalization in Supervised Learning
The randomized-feature approach has been successfully employed in large-...
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11/14/2017
On Optimal Generalizability in Parametric Learning
We consider the parametric learning problem, where the objective of the ...
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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....
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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...
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09/09/2016
Distributed Online Optimization in Dynamic Environments Using Mirror Descent
This work addresses decentralized online optimization in non-stationary ...
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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, ...
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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 ...
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03/11/2015
Switching to Learn
A network of agents attempt to learn some unknown state of the world dra...
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01/26/2015
Online Optimization : Competing with Dynamic Comparators
Recent literature on online learning has focused on developing adaptive ...
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09/30/2014
Distributed Detection : Finite-time Analysis and Impact of Network Topology
This paper addresses the problem of distributed detection in multi-agent...
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10/01/2013
Online Learning of Dynamic Parameters in Social Networks
This paper addresses the problem of online learning in a dynamic setting...
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09/10/2013