Ali Jadbabaie

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MIT ∙ University of Pennsylvania

JR East Professor of Engineering at Massachusetts Institute of Technology

A General Framework for Distributed Inference with Uncertain Models

This paper studies the problem of distributed classification with a netw...
11/20/2020 ∙ by James Z. Hare, et al. ∙ 3 ∙ share

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Gradient-Based Empirical Risk Minimization using Local Polynomial Regression

In this paper, we consider the problem of empirical risk minimization (E...
11/04/2020 ∙ by Ali Jadbabaie, et al. ∙ 8 ∙ share

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A Distributed Cubic-Regularized Newton Method for Smooth Convex Optimization over Networks

We propose a distributed, cubic-regularized Newton method for large-scal...
07/07/2020 ∙ by César A. Uribe, et al. ∙ 10 ∙ share

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GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models

Generative adversarial networks (GANs) learn the distribution of observe...
06/18/2020 ∙ by Farzan Farnia, et al. ∙ 35 ∙ share

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Robust Federated Learning: The Case of Affine Distribution Shifts

Federated learning is a distributed paradigm that aims at training model...
06/16/2020 ∙ by Amirhossein Reisizadeh, et al. ∙ 9 ∙ share

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Estimation of Skill Distributions

In this paper, we study the problem of learning the skill distribution o...
06/15/2020 ∙ by Ali Jadbabaie, et al. ∙ 5 ∙ share

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Stochastic Optimization with Non-stationary Noise

We investigate stochastic optimization problems under relaxed assumption...
06/08/2020 ∙ by Jingzhao Zhang, et al. ∙ 0 ∙ share

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A Separation Theorem for Joint Sensor and Actuator Scheduling with Guaranteed Performance Bounds

We study the problem of jointly designing a sparse sensor and actuator s...
05/06/2020 ∙ by Milad Siami, et al. ∙ 0 ∙ share

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On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions

We provide the first non-asymptotic analysis for finding stationary poin...
02/10/2020 ∙ by Jingzhao Zhang, et al. ∙ 0 ∙ share

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Competitive Contagion with Sparse Seeding

This paper studies a strategic model of marketing and product diffusion ...
12/17/2019 ∙ by Milad Siami, et al. ∙ 0 ∙ share

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Non-Bayesian Social Learning with Gaussian Uncertain Models

Non-Bayesian social learning theory provides a framework for distributed...
10/24/2019 ∙ by James Z. Hare, et al. ∙ 0 ∙ share

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FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization

Federated learning is a new distributed machine learning approach, where...
09/28/2019 ∙ by Amirhossein Reisizadeh, et al. ∙ 18 ∙ share

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Robust and Adaptive Sequential Submodular Optimization

Emerging applications of control, estimation, and machine learning, rang...
09/25/2019 ∙ by Vasileios Tzoumas, et al. ∙ 0 ∙ share

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Non-Bayesian Social Learning with Uncertain Models over Time-Varying Directed Graphs

We study the problem of non-Bayesian social learning with uncertain mode...
09/10/2019 ∙ by César A. Uribe, et al. ∙ 0 ∙ share

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Non-Bayesian Social Learning with Uncertain Models

Non-Bayesian social learning theory provides a framework that models dis...
09/09/2019 ∙ by James Z. Hare, et al. ∙ 0 ∙ share

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Are deep ResNets provably better than linear predictors?

Recently, a residual network (ResNet) with a single residual block has b...
07/09/2019 ∙ by Chulhee Yun, et al. ∙ 2 ∙ share

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Analysis of Gradient Clipping and Adaptive Scaling with a Relaxed Smoothness Condition

We provide a theoretical explanation for the fast convergence of gradien...
05/28/2019 ∙ by Jingzhao Zhang, et al. ∙ 0 ∙ share

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On Increasing Self-Confidence in Non-Bayesian Social Learning over Time-Varying Directed Graphs

We study the convergence of the log-linear non-Bayesian social learning ...
12/24/2018 ∙ by César A. Uribe, et al. ∙ 0 ∙ share

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Finite sample expressive power of small-width ReLU networks

We study universal finite sample expressivity of neural networks, define...
10/17/2018 ∙ by Chulhee Yun, et al. ∙ 12 ∙ share

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Efficiently testing local optimality and escaping saddles for ReLU networks

We provide a theoretical algorithm for checking local optimality and esc...
09/28/2018 ∙ by Chulhee Yun, et al. ∙ 18 ∙ share

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Escaping Saddle Points in Constrained Optimization

In this paper, we focus on escaping from saddle points in smooth nonconv...
09/06/2018 ∙ by Aryan Mokhtari, et al. ∙ 0 ∙ share

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Blind Community Detection from Low-rank Excitations of a Graph Filter

This paper considers a novel framework to detect communities in a graph ...
09/05/2018 ∙ by Hoi-To Wai, et al. ∙ 0 ∙ share

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Reasoning in Bayesian Opinion Exchange Networks Is PSPACE-Hard

We study the Bayesian model of opinion exchange of fully rational agents...
09/04/2018 ∙ by Jan Hązła, et al. ∙ 0 ∙ share

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Random Walks on Simplicial Complexes and the normalized Hodge Laplacian

Modeling complex systems and data with graphs has been a mainstay of the...
07/13/2018 ∙ by Michael T. Schaub, et al. ∙ 0 ∙ share

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Direct Runge-Kutta Discretization Achieves Acceleration

We study gradient-based optimization methods obtained by directly discre...
05/01/2018 ∙ by Jingzhao Zhang, et al. ∙ 0 ∙ share

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Resilient Non-Submodular Maximization over Matroid Constraints

Applications in control, robotics, and optimization motivate the design ...
04/02/2018 ∙ by Vasileios Tzoumas, et al. ∙ 0 ∙ share

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Resilient Monotone Sequential Maximization

Applications in machine learning, optimization, and control require the ...
03/21/2018 ∙ by Vasileios Tzoumas, et al. ∙ 0 ∙ share

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LQG Control and Sensing Co-design

Linear-Quadratic-Gaussian (LQG) control is concerned with the design of ...
02/23/2018 ∙ by Vasileios Tzoumas, et al. ∙ 0 ∙ share

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Control and Sensing Co-design

Linear-Quadratic-Gaussian (LQG) control is concerned with the design of ...
02/23/2018 ∙ by Vasileios Tzoumas, et al. ∙ 0 ∙ share

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Simplicial Closure and Higher-order Link Prediction

Networks provide a powerful formalism for modeling complex systems, by r...
02/20/2018 ∙ by Austin R. Benson, et al. ∙ 0 ∙ share

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A Critical View of Global Optimality in Deep Learning

We investigate the loss surface of deep linear and nonlinear neural netw...
02/10/2018 ∙ by Chulhee Yun, et al. ∙ 0 ∙ share

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On the Limited Communication Analysis and Design for Decentralized Estimation

This paper pertains to the analysis and design of decentralized estimati...
01/17/2018 ∙ by Andreea B. Alexandru, et al. ∙ 0 ∙ share

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Global optimality conditions for deep neural networks

We study the error landscape of deep linear and nonlinear neural network...
07/08/2017 ∙ by Chulhee Yun, et al. ∙ 0 ∙ share

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Bayesian Group Decisions: Algorithms and Complexity

We address the computations that Bayesian agents undertake to realize th...
05/12/2017 ∙ by Ali Jadbabaie, et al. ∙ 0 ∙ share

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Resilient Monotone Submodular Function Maximization

In this paper, we focus on applications in machine learning, optimizatio...
03/21/2017 ∙ by Vasileios Tzoumas, et al. ∙ 0 ∙ share

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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...
02/21/2017 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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Distributed Estimation and Learning over Heterogeneous Networks

We consider several estimation and learning problems that networked agen...
11/10/2016 ∙ by M. Amin Rahimian, et al. ∙ 0 ∙ share

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Distributed Online Optimization in Dynamic Environments Using Mirror Descent

This work addresses decentralized online optimization in non-stationary ...
09/09/2016 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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Learning without Recall: A Case for Log-Linear Learning

We analyze a model of learning and belief formation in networks in which...
09/30/2015 ∙ by Mohammad Amin Rahimian, et al. ∙ 0 ∙ share

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Learning without Recall by Random Walks on Directed Graphs

We consider a network of agents that aim to learn some unknown state of ...
09/14/2015 ∙ by Mohammad Amin Rahimian, et al. ∙ 0 ∙ share

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Switching to Learn

A network of agents attempt to learn some unknown state of the world dra...
03/11/2015 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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Online Optimization : Competing with Dynamic Comparators

Recent literature on online learning has focused on developing adaptive ...
01/26/2015 ∙ by Ali Jadbabaie, et al. ∙ 0 ∙ share

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

This paper addresses the problem of distributed detection in multi-agent...
09/30/2014 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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Online Learning of Dynamic Parameters in Social Networks

This paper addresses the problem of online learning in a dynamic setting...
10/01/2013 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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Exponentially Fast Parameter Estimation in Networks Using Distributed Dual Averaging

In this paper we present an optimization-based view of distributed param...
09/10/2013 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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Ali Jadbabaie

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