Georgios B. Giannakis

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University of Minnesota

Endowed Chair Professor and Director at University of Minnesota

Bayesian Semi-supervised Crowdsourcing

Crowdsourcing has emerged as a powerful paradigm for efficiently labelin...
12/20/2020 ∙ by Panagiotis A. Traganitis, et al. ∙ 11 ∙ share

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Adversarial Linear Contextual Bandits with Graph-Structured Side Observations

This paper studies the adversarial graphical contextual bandits, a varia...
12/10/2020 ∙ by Lingda Wang, et al. ∙ 6 ∙ share

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Enhancing Parameter-Free Frank Wolfe with an Extra Subproblem

Aiming at convex optimization under structural constraints, this work in...
12/09/2020 ∙ by Bingcong Li, et al. ∙ 6 ∙ share

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How Does Momentum Help Frank Wolfe?

We unveil the connections between Frank Wolfe (FW) type algorithms and t...
06/19/2020 ∙ by Bingcong Li, et al. ∙ 0 ∙ share

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Communication-Efficient Robust Federated Learning Over Heterogeneous Datasets

This work investigates fault-resilient federated learning when the data ...
06/17/2020 ∙ by Yanjie Dong, et al. ∙ 11 ∙ share

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Tensor Graph Convolutional Networks for Multi-relational and Robust Learning

The era of "data deluge" has sparked renewed interest in graph-based lea...
03/15/2020 ∙ by Vassilis N. Ioannidis, et al. ∙ 48 ∙ share

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Efficient and Stable Graph Scattering Transforms via Pruning

Graph convolutional networks (GCNs) have well-documented performance in ...
01/27/2020 ∙ by Vassilis N. Ioannidis, et al. ∙ 0 ∙ share

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Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks

This paper deals with distributed finite-sum optimization for learning o...
12/29/2019 ∙ by Zhaoxian Wu, et al. ∙ 21 ∙ share

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Learning Connectivity and Higher-order Interactions in Radial Distribution Grids

To perform any meaningful optimization task, distribution grid operators...
11/08/2019 ∙ by Qiuling Yang, et al. ∙ 0 ∙ share

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Finite-Sample Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation

Motivated by the emerging use of multi-agent reinforcement learning (MAR...
11/03/2019 ∙ by Jun Sun, et al. ∙ 18 ∙ share

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A Statistical Learning Approach to Reactive Power Control in Distribution Systems

Pronounced variability due to the growth of renewable energy sources, fl...
10/25/2019 ∙ by Qiuling Yang, et al. ∙ 5 ∙ share

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Edge Dithering for Robust Adaptive Graph Convolutional Networks

Graph convolutional networks (GCNs) are vulnerable to perturbations of t...
10/21/2019 ∙ by Vassilis N. Ioannidis, et al. ∙ 9 ∙ share

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GraphSAC: Detecting anomalies in large-scale graphs

A graph-based sampling and consensus (GraphSAC) approach is introduced t...
10/21/2019 ∙ by Vassilis N. Ioannidis, et al. ∙ 28 ∙ share

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Adaptive Step Sizes in Variance Reduction via Regularization

The main goal of this work is equipping convex and nonconvex problems wi...
10/15/2019 ∙ by Bingcong Li, et al. ∙ 30 ∙ share

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Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients

The present paper develops a novel aggregated gradient approach for dist...
09/17/2019 ∙ by Jun Sun, et al. ∙ 1 ∙ share

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A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation

Motivated by the widespread use of temporal-difference (TD-) and Q-learn...
09/10/2019 ∙ by Gang Wang, et al. ∙ 13 ∙ share

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A Variational Bayes Approach to Adaptive Radio Tomography

Radio tomographic imaging (RTI) is an emerging technology for localizati...
09/05/2019 ∙ by Donghoon Lee, et al. ∙ 10 ∙ share

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Almost Tune-Free Variance Reduction

The variance reduction class of algorithms including the representative ...
08/25/2019 ∙ by Bingcong Li, et al. ∙ 2 ∙ share

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Unsupervised Ensemble Classification with Dependent Data

Ensemble learning, the machine learning paradigm where multiple algorith...
06/22/2019 ∙ by Panagiotis A. Traganitis, et al. ∙ 7 ∙ share

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Generalization error bounds for kernel matrix completion and extrapolation

Prior information can be incorporated in matrix completion to improve es...
06/20/2019 ∙ by Pere Giménez-Febrer, et al. ∙ 4 ∙ share

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On the Convergence of SARAH and Beyond

The main theme of this work is a unifying algorithm, abbreviated as L2S,...
06/05/2019 ∙ by Bingcong Li, et al. ∙ 1 ∙ share

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Tight Linear Convergence Rate of ADMM for Decentralized Optimization

The present paper considers leveraging network topology information to i...
05/24/2019 ∙ by Meng Ma, et al. ∙ 0 ∙ share

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Minimum Uncertainty Based Detection of Adversaries in Deep Neural Networks

Despite their unprecedented performance in various domains, utilization ...
04/05/2019 ∙ by Fatemeh Sheikholeslami, et al. ∙ 0 ∙ share

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Adaptive Caching via Deep Reinforcement Learning

Caching is envisioned to play a critical role in next-generation content...
02/27/2019 ∙ by Alireza Sadeghi, et al. ∙ 0 ∙ share

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Distributed Network Caching via Dynamic Programming

Next-generation communication networks are envisioned to extensively uti...
02/19/2019 ∙ by Alireza Sadeghi, et al. ∙ 0 ∙ share

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Reinforcement Learning for Adaptive Caching with Dynamic Storage Pricing

Small base stations (SBs) of fifth-generation (5G) cellular networks are...
12/17/2018 ∙ by Alireza Sadeghi, et al. ∙ 0 ∙ share

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Communication-Efficient Distributed Reinforcement Learning

This paper studies the distributed reinforcement learning (DRL) problem ...
12/07/2018 ∙ by Tianyi Chen, et al. ∙ 0 ∙ share

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Online Graph-Adaptive Learning with Scalability and Privacy

Graphs are widely adopted for modeling complex systems, including financ...
12/03/2018 ∙ by Yanning Shen, et al. ∙ 0 ∙ share

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Graph Multiview Canonical Correlation Analysis

Multiview canonical correlation analysis (MCCA) seeks latent low-dimensi...
11/29/2018 ∙ by Jia Chen, et al. ∙ 0 ∙ share

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Adaptive-similarity node embedding for scalable learning over graphs

Node embedding is the task of extracting informative and descriptive fea...
11/27/2018 ∙ by Dimitris Berberidis, et al. ∙ 0 ∙ share

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Real-time Power System State Estimation and Forecasting via Deep Neural Networks

Contemporary smart power grids are being challenged by rapid voltage flu...
11/15/2018 ∙ by Liang Zhang, et al. ∙ 0 ∙ share

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RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets

In this paper, we propose a class of robust stochastic subgradient metho...
11/09/2018 ∙ by Liping Li, et al. ∙ 0 ∙ share

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A Recurrent Graph Neural Network for Multi-Relational Data

The era of data deluge has sparked the interest in graph-based learning ...
11/05/2018 ∙ by Vassilis N. Ioannidis, et al. ∙ 0 ∙ share

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Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability

Internet-of-Things (IoT) envisions an intelligent infrastructure of netw...
10/27/2018 ∙ by Tianyi Chen, et al. ∙ 0 ∙ share

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Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection

Joint analysis of data from multiple information repositories facilitate...
09/22/2018 ∙ by Vassilis N. Ioannidis, et al. ∙ 0 ∙ share

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Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization

Neural networks with ReLU activations have achieved great empirical succ...
08/14/2018 ∙ by Gang Wang, et al. ∙ 6 ∙ share

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Matrix completion and extrapolation via kernel regression

Matrix completion and extrapolation (MCEX) are dealt with here over repr...
08/01/2018 ∙ by Pere Giménez-Febrer, et al. ∙ 0 ∙ share

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Delayed Bandit Online Learning with Unknown Delays

This paper studies bandit learning problems with delayed feedback, which...
07/09/2018 ∙ by Bingcong Li, et al. ∙ 2 ∙ share

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LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning

This paper presents a new class of gradient methods for distributed mach...
05/25/2018 ∙ by Tianyi Chen, et al. ∙ 0 ∙ share

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Semi-Blind Inference of Topologies and Dynamical Processes over Graphs

Network science provides valuable insights across numerous disciplines i...
05/16/2018 ∙ by Vassilis N. Ioannidis, et al. ∙ 0 ∙ share

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Nonlinear Dimensionality Reduction for Discriminative Analytics of Multiple Datasets

Principal component analysis (PCA) is widely used for feature extraction...
05/15/2018 ∙ by Jia Chen, et al. ∙ 0 ∙ share

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Secure Mobile Edge Computing in IoT via Collaborative Online Learning

To accommodate heterogeneous tasks in Internet of Things (IoT), a new co...
05/09/2018 ∙ by Bingcong Li, et al. ∙ 0 ∙ share

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Multi-Timescale Online Optimization of Network Function Virtualization for Service Chaining

Network Function Virtualization (NFV) can cost-efficiently provide netwo...
04/19/2018 ∙ by Xiaojing Chen, et al. ∙ 0 ∙ share

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Fast Decentralized Optimization over Networks

The present work introduces the hybrid consensus alternating direction m...
04/06/2018 ∙ by Meng Ma, et al. ∙ 0 ∙ share

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Adaptive Bayesian Radio Tomography

Radio tomographic imaging (RTI) is an emerging technology to locate phys...
04/06/2018 ∙ by Donghoon Lee, et al. ∙ 0 ∙ share

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Adaptive Diffusions for Scalable Learning over Graphs

Diffusion-based classifiers such as those relying on the Personalized Pa...
04/05/2018 ∙ by Dimitris Berberidis, et al. ∙ 0 ∙ share

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Canonical Correlation Analysis of Datasets with a Common Source Graph

Canonical correlation analysis (CCA) is a powerful technique for discove...
03/27/2018 ∙ by Jia Chen, et al. ∙ 0 ∙ share

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Nonlinear Dimensionality Reduction on Graphs

In this era of data deluge, many signal processing and machine learning ...
01/29/2018 ∙ by Yanning Shen, et al. ∙ 0 ∙ share

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Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics

Kernel-based methods exhibit well-documented performance in various nonl...
12/28/2017 ∙ by Yanning Shen, et al. ∙ 0 ∙ share

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Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments

Kernel-based methods exhibit well-documented performance in various nonl...
12/28/2017 ∙ by Yanning Shen, et al. ∙ 0 ∙ share

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Georgios B. Giannakis

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