Navid Azizan

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 39

Top Topics

Top Venues

SIGMETRICS Perform. Evaluation Rev.

Publications

Kaveh Alimohammadi, Hao Wang, Ojas Gulati, Akash Srivastava, Navid Azizan
Adapting Differentially Private Synthetic Data to Relational Databases. CoRR (2024)
Sunbochen Tang, Haoyuan Sun, Navid Azizan
Meta-Learning for Adaptive Control with Automated Mirror Descent. CoRR (2024)
Devansh Jalota, Haoyuan Sun, Navid Azizan
Online Learning for Equilibrium Pricing in Markets under Incomplete Information. CDC (2023)
Boris Velasevic, Rohit Parasnis, Christopher G. Brinton, Navid Azizan
On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers. CDC (2023)
Haoyuan Sun, Navid Azizan, Akash Srivastava, Hao Wang
Private Synthetic Data Meets Ensemble Learning. CoRR (2023)
Devansh Jalota, Haoyuan Sun, Navid Azizan
Online Learning for Equilibrium Pricing in Markets under Incomplete Information. CoRR (2023)
Youngjae Min, Spencer M. Richards, Navid Azizan
Data-Driven Control with Inherent Lyapunov Stability. CDC (2023)
Benjamin Wright, Youngjae Min, Jeremy Bernstein, Navid Azizan
SketchOGD: Memory-Efficient Continual Learning. CoRR (2023)
Devansh Jalota, Karthik Gopalakrishnan, Navid Azizan, Ramesh Johari, Marco Pavone
Online Learning for Traffic Routing under Unknown Preferences. AISTATS (2023)
Young-Jin Park, Hao Wang, Shervin Ardeshir, Navid Azizan
Representation Reliability and Its Impact on Downstream Tasks. CoRR (2023)
Spencer M. Richards, Navid Azizan, Jean-Jacques E. Slotine, Marco Pavone
Control-oriented meta-learning. Int. J. Robotics Res. 42 (10) (2023)
Spencer M. Richards, Jean-Jacques E. Slotine, Navid Azizan, Marco Pavone
Learning Control-Oriented Dynamical Structure from Data. CoRR (2023)
Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan, Yisong Yue
Automatic Gradient Descent: Deep Learning without Hyperparameters. CoRR (2023)
Spencer M. Richards, Jean-Jacques E. Slotine, Navid Azizan, Marco Pavone
Learning Control-Oriented Dynamical Structure from Data. ICML (2023)
Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan
A Unified Approach to Controlling Implicit Regularization via Mirror Descent. CoRR (2023)
Boris Velasevic, Rohit Parasnis, Christopher G. Brinton, Navid Azizan
On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers. CoRR (2023)
Youngjae Min, Spencer M. Richards, Navid Azizan
Data-Driven Control with Inherent Lyapunov Stability. CoRR (2023)
Spencer M. Richards, Navid Azizan, Jean-Jacques E. Slotine, Marco Pavone
Control-oriented meta-learning. CoRR (2022)
Navid Azizan, Sahin Lale, Babak Hassibi
Stochastic Mirror Descent on Overparameterized Nonlinear Models. IEEE Trans. Neural Networks Learn. Syst. 33 (12) (2022)
Navid Azizan, Sahin Lale, Babak Hassibi
Explicit Regularization via Regularizer Mirror Descent. CoRR (2022)
Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis, Navid Azizan
Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently. NeurIPS (2022)
Robin A. Brown, Edward Schmerling, Navid Azizan, Marco Pavone
A Unified View of SDP-based Neural Network Verification through Completely Positive Programming. AISTATS (2022)
Shervin Ardeshir, Navid Azizan
Uncertainty in Contrastive Learning: On the Predictability of Downstream Performance. CoRR (2022)
Cesar Almecija, Apoorva Sharma, Navid Azizan
Uncertainty-Aware Meta-Learning for Multimodal Task Distributions. CoRR (2022)
Robin A. Brown, Edward Schmerling, Navid Azizan, Marco Pavone
A Unified View of SDP-based Neural Network Verification through Completely Positive Programming. CoRR (2022)
Youngjae Min, Kwangjun Ahn, Navid Azizan
One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares. CoRR (2022)
Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis, Navid Azizan
Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently. CoRR (2022)
Youngjae Min, Kwangjun Ahn, Navid Azizan
One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares. CDC (2022)
Devansh Jalota, Karthik Gopalakrishnan, Navid Azizan, Ramesh Johari, Marco Pavone
Online Learning for Traffic Routing under Unknown Preferences. CoRR (2022)
Spencer M. Richards, Navid Azizan, Jean-Jacques E. Slotine, Marco Pavone
Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems. Robotics: Science and Systems (2021)
Spencer M. Richards, Navid Azizan, Jean-Jacques E. Slotine, Marco Pavone
Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems. CoRR (2021)
Apoorva Sharma, Navid Azizan, Marco Pavone
Sketching Curvature for Efficient Out-of-Distribution Detection for Deep Neural Networks. CoRR (2021)
Apoorva Sharma, Navid Azizan, Marco Pavone
Sketching curvature for efficient out-of-distribution detection for deep neural networks. UAI (2021)
Navid Azizan, Yu Su, Krishnamurthy Dvijotham, Adam Wierman
Optimal Pricing in Markets with Nonconvex Costs. Oper. Res. 68 (2) (2020)
Navid Azizan, Sahin Lale, Babak Hassibi
A Study of Generalization of Stochastic Mirror Descent Algorithms on Overparameterized Nonlinear Models. ICASSP (2020)
Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li
Orthogonal Gradient Descent for Continual Learning. AISTATS (2020)
Navid Azizan, Babak Hassibi
A Stochastic Interpretation of Stochastic Mirror Descent: Risk-Sensitive Optimality. CDC (2019)
Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li
Orthogonal Gradient Descent for Continual Learning. CoRR (2019)
Navid Azizan
Optimization Algorithms for Large-Scale Systems: From Deep Learning to Energy Markets. SIGMETRICS Perform. Evaluation Rev. 47 (3) (2019)