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02/18/2023
The Generalization Error of Stochastic Mirror Descent on Over-Parametrized Linear Models
Despite being highly over-parametrized, and having the ability to fully ...
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02/13/2023
Precise Asymptotic Analysis of Deep Random Feature Models
We provide exact asymptotic expressions for the performance of regressio...
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10/27/2022
Stochastic Mirror Descent in Average Ensemble Models
The stochastic mirror descent (SMD) algorithm is a general class of trai...
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07/21/2022
Feedback capacity of Gaussian channels with memory
We consider the feedback capacity of a MIMO channel whose channel output...
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06/17/2022
Thompson Sampling Achieves Õ(√(T)) Regret in Linear Quadratic Control
Thompson Sampling (TS) is an efficient method for decision-making under ...
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02/22/2022
Explicit Regularization via Regularizer Mirror Descent
Despite perfectly interpolating the training data, deep neural networks ...
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10/24/2021
Online estimation and control with optimal pathlength regret
A natural goal when designing online learning algorithms for non-station...
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10/05/2021
How to Query An Oracle? Efficient Strategies to Label Data
We consider the basic problem of querying an expert oracle for labeling ...
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09/25/2021
Reducing the LQG Cost with Minimal Communication
We study the linear quadratic Gaussian (LQG) control problem, in which t...
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08/26/2021
Finite-time System Identification and Adaptive Control in Autoregressive Exogenous Systems
Autoregressive exogenous (ARX) systems are the general class of input-ou...
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07/28/2021
Competitive Control
We consider control from the perspective of competitive analysis. Unlike...
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06/22/2021
Regret-optimal Estimation and Control
We consider estimation and control in linear time-varying dynamical syst...
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06/03/2021
Feedback Capacity of MIMO Gaussian Channels
Finding a computable expression for the feedback capacity of additive ch...
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05/04/2021
Regret-Optimal Full-Information Control
We consider the infinite-horizon, discrete-time full-information control...
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01/25/2021
Regret-Optimal Filtering
We consider the problem of filtering in linear state-space models (e.g.,...
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12/08/2020
Stability and Identification of Random Asynchronous Linear Time-Invariant Systems
In many computational tasks and dynamical systems, asynchrony and random...
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10/29/2020
Robustifying Binary Classification to Adversarial Perturbation
Despite the enormous success of machine learning models in various appli...
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10/29/2020
The Performance Analysis of Generalized Margin Maximizer (GMM) on Separable Data
Logistic models are commonly used for binary classification tasks. The s...
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10/20/2020
Regret-optimal control in dynamic environments
We consider the control of linear time-varying dynamical systems from th...
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07/23/2020
Explore More and Improve Regret in Linear Quadratic Regulators
Stabilizing the unknown dynamics of a control system and minimizing regr...
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04/29/2020
Support Constrained Generator Matrices of Gabidulin Codes in Characteristic Zero
Gabidulin codes over fields of characteristic zero were recently constru...
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03/25/2020
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems
We study the problem of adaptive control in partially observable linear ...
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03/12/2020
Regret Bound of Adaptive Control in Linear Quadratic Gaussian (LQG) Systems
We study the problem of adaptive control in partially observable linear ...
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02/07/2020
The Power of Linear Controllers in LQR Control
The Linear Quadratic Regulator (LQR) framework considers the problem of ...
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02/06/2020
Achieving the fundamental convergence-communication tradeoff with Differentially Quantized Gradient Descent
The problem of reducing the communication cost in distributed training t...
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01/31/2020
Regret Minimization in Partially Observable Linear Quadratic Control
We study the problem of regret minimization in partially observable line...
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06/20/2019
Universality in Learning from Linear Measurements
We study the problem of recovering a structured signal from independentl...
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06/10/2019
Stochastic Mirror Descent on Overparameterized Nonlinear Models: Convergence, Implicit Regularization, and Generalization
Most modern learning problems are highly overparameterized, meaning that...
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06/10/2019
The Impact of Regularization on High-dimensional Logistic Regression
Logistic regression is commonly used for modeling dichotomous outcomes. ...
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04/03/2019
A Stochastic Interpretation of Stochastic Mirror Descent: Risk-Sensitive Optimality
Stochastic mirror descent (SMD) is a fairly new family of algorithms tha...
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03/22/2019
Gabidulin Codes with Support Constrained Generator Matrices
Gabidulin codes are the only known general construction of linear codes ...
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02/08/2019
MOCZ for Blind Short-Packet Communication: Some Practical Aspects
We will investigate practical aspects for a recently introduced blind (n...
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01/28/2019
Stochastic Linear Bandits with Hidden Low Rank Structure
High-dimensional representations often have a lower dimensional underlyi...
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09/13/2018
Algorithms for Optimal Control with Fixed-Rate Feedback
We consider a discrete-time linear quadratic Gaussian networked control ...
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06/04/2018
Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization
Stochastic descent methods (of the gradient and mirror varieties) have b...
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05/21/2018
Noncoherent Short-Packet Communication via Modulation on Conjugated Zeros
We introduce a novel blind (noncoherent) communication scheme, called mo...
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03/10/2018
Optimum Linear Codes with Support Constraints over Small Fields
We consider the problem of designing optimal linear codes (in terms of h...
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01/24/2018
Further Progress on the GM-MDS Conjecture for Reed-Solomon Codes
Designing good error correcting codes whose generator matrix has a suppo...
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01/20/2018
A Precise Analysis of PhaseMax in Phase Retrieval
Recovering an unknown complex signal from the magnitude of linear combin...
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11/30/2017
Symbol Error Rate Performance of Box-relaxation Decoders in Massive MIMO
The maximum-likelihood (ML) decoder for symbol detection in large multip...
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01/28/2017
Entropic Causality and Greedy Minimum Entropy Coupling
We study the problem of identifying the causal relationship between two ...
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11/12/2016
Entropic Causal Inference
We consider the problem of identifying the causal direction between two ...
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04/27/2011
Finding Dense Clusters via "Low Rank + Sparse" Decomposition
Finding "densely connected clusters" in a graph is in general an importa...
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11/29/2010
New Null Space Results and Recovery Thresholds for Matrix Rank Minimization
Nuclear norm minimization (NNM) has recently gained significant attentio...
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09/07/2008