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06/02/2023
Smooth Model Predictive Control with Applications to Statistical Learning
Statistical learning theory and high dimensional statistics have had a t...
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06/02/2023
Convex and Non-Convex Optimization under Generalized Smoothness
Classical analysis of convex and non-convex optimization methods often r...
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05/25/2023
Demystifying Oversmoothing in Attention-Based Graph Neural Networks
Oversmoothing in Graph Neural Networks (GNNs) refers to the phenomenon w...
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05/25/2023
How to escape sharp minima
Modern machine learning applications have seen a remarkable success of o...
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04/27/2023
Convergence of Adam Under Relaxed Assumptions
In this paper, we provide a rigorous proof of convergence of the Adaptiv...
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03/02/2023
Variance-reduced Clipping for Non-convex Optimization
Gradient clipping is a standard training technique used in deep learning...
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12/21/2022
A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks
A central challenge of building more powerful Graph Neural Networks (GNN...
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10/17/2022
Model Predictive Control via On-Policy Imitation Learning
In this paper, we leverage the rapid advances in imitation learning, a t...
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10/04/2022
Link Partitioning on Simplicial Complexes Using Higher-Order Laplacians
Link partitioning is a popular approach in network science used for disc...
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07/22/2022
Generalizing Homophily to Simplicial Complexes
Group interactions occur frequently in social settings, yet their proper...
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06/16/2022
Gradient Descent for Low-Rank Functions
Several recent empirical studies demonstrate that important machine lear...
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04/03/2022
Byzantine-Robust Federated Linear Bandits
In this paper, we study a linear bandit optimization problem in a federa...
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03/29/2022
Current Implicit Policies May Not Eradicate COVID-19
Successful predictive modeling of epidemics requires an understanding of...
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01/07/2022
Unifying Epidemic Models with Mixtures
The COVID-19 pandemic has emphasized the need for a robust understanding...
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01/06/2022
Federated Optimization of Smooth Loss Functions
In this work, we study empirical risk minimization (ERM) within a federa...
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12/29/2021
Time varying regression with hidden linear dynamics
We revisit a model for time-varying linear regression that assumes the u...
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10/12/2021
On Convergence of Training Loss Without Reaching Stationary Points
It is a well-known fact that nonconvex optimization is computationally i...
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07/25/2021
In Defense of Fluid Democracy
Fluid democracy is a voting paradigm that allows voters to choose betwee...
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04/18/2021
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization
We provide a first-order oracle complexity lower bound for finding stati...
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03/12/2021
Can Single-Shuffle SGD be Better than Reshuffling SGD and GD?
We propose matrix norm inequalities that extend the Recht-Ré (2012) conj...
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12/04/2020
Network Group Testing
We consider the problem of identifying infected individuals in a populat...
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11/20/2020
A General Framework for Distributed Inference with Uncertain Models
This paper studies the problem of distributed classification with a netw...
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11/04/2020
Gradient-Based Empirical Risk Minimization using Local Polynomial Regression
In this paper, we consider the problem of empirical risk minimization (E...
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07/07/2020
A Distributed Cubic-Regularized Newton Method for Smooth Convex Optimization over Networks
We propose a distributed, cubic-regularized Newton method for large-scal...
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06/18/2020
GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models
Generative adversarial networks (GANs) learn the distribution of observe...
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06/16/2020
Robust Federated Learning: The Case of Affine Distribution Shifts
Federated learning is a distributed paradigm that aims at training model...
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06/15/2020
Estimation of Skill Distributions
In this paper, we study the problem of learning the skill distribution o...
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06/08/2020
Stochastic Optimization with Non-stationary Noise
We investigate stochastic optimization problems under relaxed assumption...
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05/06/2020
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...
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02/10/2020
On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions
We provide the first non-asymptotic analysis for finding stationary poin...
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12/17/2019
Competitive Contagion with Sparse Seeding
This paper studies a strategic model of marketing and product diffusion ...
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10/24/2019
Non-Bayesian Social Learning with Gaussian Uncertain Models
Non-Bayesian social learning theory provides a framework for distributed...
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09/28/2019
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Federated learning is a new distributed machine learning approach, where...
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09/25/2019
Robust and Adaptive Sequential Submodular Optimization
Emerging applications of control, estimation, and machine learning, rang...
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09/10/2019
Non-Bayesian Social Learning with Uncertain Models over Time-Varying Directed Graphs
We study the problem of non-Bayesian social learning with uncertain mode...
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09/09/2019
Non-Bayesian Social Learning with Uncertain Models
Non-Bayesian social learning theory provides a framework that models dis...
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07/09/2019
Are deep ResNets provably better than linear predictors?
Recently, a residual network (ResNet) with a single residual block has b...
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05/28/2019
Analysis of Gradient Clipping and Adaptive Scaling with a Relaxed Smoothness Condition
We provide a theoretical explanation for the fast convergence of gradien...
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12/24/2018
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 ...
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10/17/2018
Finite sample expressive power of small-width ReLU networks
We study universal finite sample expressivity of neural networks, define...
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09/28/2018
Efficiently testing local optimality and escaping saddles for ReLU networks
We provide a theoretical algorithm for checking local optimality and esc...
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09/06/2018
Escaping Saddle Points in Constrained Optimization
In this paper, we focus on escaping from saddle points in smooth nonconv...
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09/05/2018
Blind Community Detection from Low-rank Excitations of a Graph Filter
This paper considers a novel framework to detect communities in a graph ...
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09/04/2018
Reasoning in Bayesian Opinion Exchange Networks Is PSPACE-Hard
We study the Bayesian model of opinion exchange of fully rational agents...
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07/13/2018
Random Walks on Simplicial Complexes and the normalized Hodge Laplacian
Modeling complex systems and data with graphs has been a mainstay of the...
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05/01/2018
Direct Runge-Kutta Discretization Achieves Acceleration
We study gradient-based optimization methods obtained by directly discre...
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04/02/2018
Resilient Non-Submodular Maximization over Matroid Constraints
Applications in control, robotics, and optimization motivate the design ...
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03/21/2018
Resilient Monotone Sequential Maximization
Applications in machine learning, optimization, and control require the ...
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02/23/2018
LQG Control and Sensing Co-design
Linear-Quadratic-Gaussian (LQG) control is concerned with the design of ...
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02/23/2018