Justin Romberg

research

∙ 04/04/2023

Scalable Online Learning of Approximate Stackelberg Solutions in Energy Trading Games with Demand Response Aggregators

In this work, a Stackelberg game theoretic framework is proposed for tra...

0 Styliani I. Kampezidou, et al. ∙

research

∙ 03/23/2023

Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems

The aim of this paper is to improve the understanding of the optimizatio...

0 Sihan Zeng, et al. ∙

research

∙ 10/10/2022

Loop Unrolled Shallow Equilibrium Regularizer (LUSER) – A Memory-Efficient Inverse Problem Solver

In inverse problems we aim to reconstruct some underlying signal of inte...

0 Peimeng Guan, et al. ∙

research

∙ 07/23/2022

A Dual Accelerated Method for Online Stochastic Distributed Averaging: From Consensus to Decentralized Policy Evaluation

Motivated by decentralized sensing and policy evaluation problems, we co...

0 Sheng Zhang, et al. ∙

research

∙ 05/27/2022

Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games

We study the problem of finding the Nash equilibrium in a two-player zer...

0 Sihan Zeng, et al. ∙

research

∙ 10/28/2021

Decentralized Feature-Distributed Optimization for Generalized Linear Models

We consider the "all-for-one" decentralized learning problem for general...

0 Brighton Ancelin, et al. ∙

research

∙ 10/28/2021

Approximately low-rank recovery from noisy and local measurements by convex program

Low-rank matrix models have been universally useful for numerous applica...

0 Kiryung Lee, et al. ∙

research

∙ 10/21/2021

Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes

We consider a discounted cost constrained Markov decision process (CMDP)...

0 Sihan Zeng, et al. ∙

research

∙ 09/29/2021

A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning

We study a novel two-time-scale stochastic gradient method for solving o...

0 Sihan Zeng, et al. ∙

research

∙ 03/22/2021

Thomson's Multitaper Method Revisited

Thomson's multitaper method estimates the power spectrum of a signal fro...

0 Santhosh Karnik, et al. ∙

research

∙ 01/26/2021

Finite Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm

Actor-critic style two-time-scale algorithms are very popular in reinfor...

0 Sajad Khodadadian, et al. ∙

research

∙ 10/28/2020

Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning

Stochastic approximation, a data-driven approach for finding the fixed p...

0 Sihan Zeng, et al. ∙

research

∙ 06/15/2020

Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification

The attention mechanism has demonstrated superior performance for infere...

0 Rakshith S Srinivasa, et al. ∙

research

∙ 06/13/2020

Sample complexity and effective dimension for regression on manifolds

We consider the theory of regression on a manifold using reproducing ker...

0 Andrew McRae, et al. ∙

research

∙ 06/08/2020

A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning

We develop a mathematical framework for solving multi-task reinforcement...

4 Sihan Zeng, et al. ∙

research

∙ 03/24/2020

Finite-Time Analysis of Stochastic Gradient Descent under Markov Randomness

Motivated by broad applications in reinforcement learning and machine le...

0 Thinh T. Doan, et al. ∙

research

∙ 03/20/2020

Localized sketching for matrix multiplication and ridge regression

We consider sketched approximate matrix multiplication and ridge regress...

0 Rakshith S Srinivasa, et al. ∙

research

∙ 11/09/2019

Hardware-aware Pruning of DNNs using LFSR-Generated Pseudo-Random Indices

Deep neural networks (DNNs) have been emerged as the state-of-the-art al...

0 Foroozan Karimzadeh, et al. ∙

research

∙ 10/25/2019

Phase Retrieval of Low-Rank Matrices by Anchored Regression

We study the low-rank phase retrieval problem, where we try to recover a...

0 Kiryung Lee, et al. ∙

research

∙ 08/26/2019

Convex Programming for Estimation in Nonlinear Recurrent Models

We propose a formulation for nonlinear recurrent models that includes si...

0 Sohail Bahmani, et al. ∙

research

∙ 07/25/2019

Finite-Time Performance of Distributed Temporal Difference Learning with Linear Function Approximation

We study the policy evaluation problem in multi-agent reinforcement lear...

0 Thinh T. Doan, et al. ∙

research

∙ 02/19/2019

Fast Compressive Sensing Recovery Using Generative Models with Structured Latent Variables

Deep learning models have significantly improved the visual quality and ...

0 Shaojie Xu, et al. ∙

research

∙ 02/19/2019

Appearance-based Gesture recognition in the compressed domain

We propose a novel appearance-based gesture recognition algorithm using ...

0 Shaojie Xu, et al. ∙

research

∙ 01/31/2019

Trading beams for bandwidth: Imaging with randomized beamforming

We study the problem of actively imaging a range-limited far-field scene...

0 Rakshith Sharma Srinivasa, et al. ∙

research

∙ 06/17/2018

Fast Convex Pruning of Deep Neural Networks

We develop a fast, tractable technique called Net-Trim for simplifying a...

0 Alireza Aghasi, et al. ∙

research

∙ 12/13/2017

ROAST: Rapid Orthogonal Approximate Slepian Transform

In this paper, we provide a Rapid Orthogonal Approximate Slepian Transfo...

0 Zhihui Zhu, et al. ∙

research

∙ 02/17/2017

Solving Equations of Random Convex Functions via Anchored Regression

We consider the question of estimating a solution to a system of equatio...

0 Sohail Bahmani, et al. ∙

research

∙ 11/16/2016

Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee

We introduce and analyze a new technique for model reduction for deep ne...

0 Alireza Aghasi, et al. ∙

research

∙ 10/13/2016

Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation

We propose a flexible convex relaxation for the phase retrieval problem ...

0 Sohail Bahmani, et al. ∙

research

∙ 05/26/2016

A Light-powered, Always-On, Smart Camera with Compressed Domain Gesture Detection

In this paper we propose an energy-efficient camera-based gesture recogn...

0 Anvesha A, et al. ∙

research

∙ 03/29/2016

Sweep Distortion Removal from THz Images via Blind Demodulation

Heavy sweep distortion induced by alignments and inter-reflections of la...

0 Alireza Aghasi, et al. ∙

research

∙ 02/23/2016

Learning Shapes by Convex Composition

We present a mathematical and algorithmic scheme for learning the princi...

0 Alireza Aghasi, et al. ∙

research

∙ 06/14/2013

Sparse Recovery of Streaming Signals Using L1-Homotopy

Most of the existing methods for sparse signal recovery assume a static ...

0 M. Salman Asif, et al. ∙

research

∙ 08/03/2012

Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization

To recover a sparse signal from an underdetermined system, we often solv...

0 M. Salman Asif, et al. ∙

Justin Romberg

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