Navid Azizan

Jean-Jacques E. Slotine

Int. J. Robotics Res., September, 2023

Private Synthetic Data Meets Ensemble Learning.

[BibT_eX]

[DOI]

CoRR, 2023

A Unified Approach to Controlling Implicit Regularization via Mirror Descent.

[BibT_eX]

[DOI]

CoRR, 2023

Representation Reliability and Its Impact on Downstream Tasks.

[BibT_eX]

[DOI]

CoRR, 2023

SketchOGD: Memory-Efficient Continual Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Automatic Gradient Descent: Deep Learning without Hyperparameters.

[BibT_eX]

[DOI]

CoRR, 2023

Learning Control-Oriented Dynamical Structure from Data.

[BibT_eX]

[DOI]

Jean-Jacques E. Slotine

Proceedings of the International Conference on Machine Learning, 2023

On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers.

[BibT_eX]

[DOI]

Boris Velasevic

Rohit Parasnis

Christopher G. Brinton

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Data-Driven Control with Inherent Lyapunov Stability.

[BibT_eX]

[DOI]

Youngjae Min

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Online Learning for Equilibrium Pricing in Markets under Incomplete Information.

[BibT_eX]

[DOI]

Devansh Jalota

Haoyuan Sun

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Online Learning for Traffic Routing under Unknown Preferences.

[BibT_eX]

[DOI]

Devansh Jalota

Karthik Gopalakrishnan

Ramesh Johari

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Stochastic Mirror Descent on Overparameterized Nonlinear Models.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2022

Uncertainty-Aware Meta-Learning for Multimodal Task Distributions.

[BibT_eX]

[DOI]

Cesar Almecija

Apoorva Sharma

CoRR, 2022

Uncertainty in Contrastive Learning: On the Predictability of Downstream Performance.

[BibT_eX]

[DOI]

Shervin Ardeshir

CoRR, 2022

Explicit Regularization via Regularizer Mirror Descent.

[BibT_eX]

[DOI]

CoRR, 2022

Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently.

[BibT_eX]

[DOI]

Haoyuan Sun

Kwangjun Ahn

Christos Thrampoulidis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares.

[BibT_eX]

[DOI]

Youngjae Min

Kwangjun Ahn

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

A Unified View of SDP-based Neural Network Verification through Completely Positive Programming.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Sketching curvature for efficient out-of-distribution detection for deep neural networks.

[BibT_eX]

[DOI]

Apoorva Sharma

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems.

[BibT_eX]

[DOI]

Jean-Jacques E. Slotine

Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

2020

Optimal Pricing in Markets with Nonconvex Costs.

[BibT_eX]

[DOI]

Yu Su

Krishnamurthy Dvijotham

Adam Wierman

Oper. Res., 2020

A Study of Generalization of Stochastic Mirror Descent Algorithms on Overparameterized Nonlinear Models.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Orthogonal Gradient Descent for Continual Learning.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Distributed Solution of Large-Scale Linear Systems via Accelerated Projection-Based Consensus.

[BibT_eX]

[DOI]

Farshad Lahouti

Amir Salman Avestimehr

IEEE Trans. Signal Process., 2019

Optimization Algorithms for Large-Scale Systems: From Deep Learning to Energy Markets.

[BibT_eX]

[DOI]

SIGMETRICS Perform. Evaluation Rev., 2019

Stochastic Mirror Descent on Overparameterized Nonlinear Models: Convergence, Implicit Regularization, and Generalization.

[BibT_eX]

[DOI]

CoRR, 2019

Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2019

Optimal Pricing in Markets with Non-Convex Costs.

[BibT_eX]

[DOI]

Yu Su

Krishnamurthy Dvijotham

Adam Wierman

Proceedings of the 2019 ACM Conference on Economics and Computation, 2019

A Stochastic Interpretation of Stochastic Mirror Descent: Risk-Sensitive Optimality.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

Improving Distributed Gradient Descent Using Reed-Solomon Codes.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2016

Opportunities for Price Manipulation by Aggregators in Electricity Markets.

[BibT_eX]

[DOI]

Niangjun Chen

Krishnamurthy Dvijotham

Adam Wierman

SIGMETRICS Perform. Evaluation Rev., 2016

Analysis of Exact and Approximated Epidemic Models over Complex Networks.

[BibT_eX]

[DOI]

Hyoung Jun Ahn

CoRR, 2016

Improved bounds on the epidemic threshold of exact SIS models on complex networks.

[BibT_eX]

[DOI]

Christos Thrampoulidis

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015

Multiscale modeling of biological communication.

[BibT_eX]

[DOI]

Paul Bogdan

Proceedings of the 2015 IEEE International Conference on Communications, 2015

SIRS epidemics on complex networks: Concurrence of exact Markov chain and approximated models.

[BibT_eX]

[DOI]