Navid Azizan - RankMe

62 papers A* 2A 5C 1Misc 1Journal 46Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection. J. Mach. Learn. Res. Aaron Alvarado Kristanto Julistiono, Davoud Ataee Tarzanagh, Navid Azizan
2026	J	`jnl`	Reverse Flow Matching: A Unified Framework for Online Reinforcement Learning with Diffusion and Flow Policies. CoRR Zeyang Li, Sunbochen Tang, Navid Azizan
2025	J	`jnl`	ATOM-CBF: Adaptive Safe Perception-Based Control under Out-of-Distribution Measurements. CoRR Kai S. Yun, Navid Azizan
2025	J	`jnl`	Activation-Informed Merging of Large Language Models. CoRR Amin Heyrani Nobari, Kaveh Alimohammadi, Ali ArjomandBigdeli, Akash Srivastava, Faez Ahmed, Navid Azizan
2025	J	`jnl`	Constrained Online Decision-Making: A Unified Framework. CoRR Haichen Hu, David Simchi-Levi, Navid Azizan
2025	J	`jnl`	ECO: Energy-Constrained Operator Learning for Chaotic Dynamics with Boundedness Guarantees. CoRR Andrea Goertzen, Sunbochen Tang, Navid Azizan
2025	J	`jnl`	Efficient Multi-Adapter LLM Serving via Cross-Model KV-Cache Reuse with Activated LoRA. CoRR Allison Li, Kristjan H. Greenewald, Thomas Parnell, Navid Azizan
2025	J	`jnl`	HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization. CoRR Zeyang Li, Kaveh Alim, Navid Azizan
2025	J	`jnl`	Hierarchical Vision-Language Planning for Multi-Step Humanoid Manipulation. CoRR André Schakkal, Ben Zandonati, Zhutian Yang, Navid Azizan
2025	J	`jnl`	In-Context Learning of Polynomial Kernel Regression in Transformers with GLU Layers. CoRR Haoyuan Sun, Ali Jadbabaie, Navid Azizan
2025	J	`jnl`	Know What You Don't Know: Uncertainty Calibration of Process Reward Models. CoRR Young-Jin Park, Kristjan H. Greenewald, Kaveh Alim, Hao Wang, Navid Azizan
2025	—	`conf`	Meta-Learning for Adaptive Control with Automated Mirror Descent. L4DC Sunbochen Tang, Haoyuan Sun, Navid Azizan
2025	J	`jnl`	Personalized Collaborative Learning with Affinity-Based Variance Reduction. CoRR Chenyu Zhang, Navid Azizan
2025	J	`jnl`	Probabilistic Forecasting for Building Energy Systems using Time-Series Foundation Models. CoRR Young Jin Park, François G. Germain, Jing Liu, Ye Wang, Toshiaki Koike-Akino, Gordon Wichern, Navid Azizan, Christopher R. Laughman, Ankush Chakrabarty
2025	J	`jnl`	Test-Time-Scaling for Zero-Shot Diagnosis with Visual-Language Reasoning. CoRR Ji Young Byun, Young-Jin Park, Navid Azizan, Rama Chellappa
2024	J	`jnl`	Adapting Differentially Private Synthetic Data to Relational Databases. CoRR Kaveh Alimohammadi, Hao Wang, Ojas Gulati, Akash Srivastava, Navid Azizan
2024	J	`jnl`	Hard-Constrained Neural Networks with Universal Approximation Guarantees. CoRR Youngjae Min, Anoopkumar Sonar, Navid Azizan
2024	J	`jnl`	Identifying Reliable Predictions in Detection Transformers. CoRR Young-Jin Park, Carson Sobolewski, Navid Azizan
2024	J	`jnl`	Learning Chaotic Dynamics with Embedded Dissipativity. CoRR Sunbochen Tang, Themistoklis Sapsis, Navid Azizan
2024	J	`jnl`	Meta-Learning for Adaptive Control with Automated Mirror Descent. CoRR Sunbochen Tang, Haoyuan Sun, Navid Azizan
2024	J	`jnl`	Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection. CoRR Aaron Alvarado Kristanto Julistiono, Davoud Ataee Tarzanagh, Navid Azizan
2024	A	`conf`	Quantifying Representation Reliability in Self-Supervised Learning Models. UAI Young-Jin Park, Hao Wang, Shervin Ardeshir, Navid Azizan
2024	J	`jnl`	Safe Multi-Agent Reinforcement Learning with Convergence to Generalized Nash Equilibrium. CoRR Zeyang Li, Navid Azizan
2024	C	`conf`	Π-ORFit: One-Pass Learning with Bregman Projection. ACC Namhoon Cho, Youngjae Min, Hyo-Sang Shin, Navid Azizan
2023	J	`jnl`	A Unified Approach to Controlling Implicit Regularization via Mirror Descent. CoRR Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan
2023	J	`jnl`	A Unified Approach to Controlling Implicit Regularization via Mirror Descent. J. Mach. Learn. Res. Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan
2023	J	`jnl`	Automatic Gradient Descent: Deep Learning without Hyperparameters. CoRR Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan, Yisong Yue
2023	J	`jnl`	Control-oriented meta-learning. Int. J. Robotics Res. Spencer M. Richards, Navid Azizan, Jean-Jacques E. Slotine, Marco Pavone
2023	—	`conf`	Data-Driven Control with Inherent Lyapunov Stability. CDC Youngjae Min, Spencer M. Richards, Navid Azizan
2023	J	`jnl`	Data-Driven Control with Inherent Lyapunov Stability. CoRR Youngjae Min, Spencer M. Richards, Navid Azizan
2023	A*	`conf`	Learning Control-Oriented Dynamical Structure from Data. ICML Spencer M. Richards, Jean-Jacques E. Slotine, Navid Azizan, Marco Pavone
2023	J	`jnl`	Learning Control-Oriented Dynamical Structure from Data. CoRR Spencer M. Richards, Jean-Jacques E. Slotine, Navid Azizan, Marco Pavone
2023	—	`conf`	On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers. CDC Boris Velasevic, Rohit Parasnis, Christopher G. Brinton, Navid Azizan
2023	J	`jnl`	On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers. CoRR Boris Velasevic, Rohit Parasnis, Christopher G. Brinton, Navid Azizan
2023	—	`conf`	Online Learning for Equilibrium Pricing in Markets under Incomplete Information. CDC Devansh Jalota, Haoyuan Sun, Navid Azizan
2023	J	`jnl`	Online Learning for Equilibrium Pricing in Markets under Incomplete Information. CoRR Devansh Jalota, Haoyuan Sun, Navid Azizan
2023	A	`conf`	Online Learning for Traffic Routing under Unknown Preferences. AISTATS Devansh Jalota, Karthik Gopalakrishnan, Navid Azizan, Ramesh Johari, Marco Pavone
2023	J	`jnl`	Private Synthetic Data Meets Ensemble Learning. CoRR Haoyuan Sun, Navid Azizan, Akash Srivastava, Hao Wang
2023	J	`jnl`	Representation Reliability and Its Impact on Downstream Tasks. CoRR Young-Jin Park, Hao Wang, Shervin Ardeshir, Navid Azizan
2023	J	`jnl`	SketchOGD: Memory-Efficient Continual Learning. CoRR Benjamin Wright, Youngjae Min, Jeremy Bernstein, Navid Azizan
2022	A	`conf`	A Unified View of SDP-based Neural Network Verification through Completely Positive Programming. AISTATS Robin A. Brown, Edward Schmerling, Navid Azizan, Marco Pavone
2022	J	`jnl`	A Unified View of SDP-based Neural Network Verification through Completely Positive Programming. CoRR Robin A. Brown, Edward Schmerling, Navid Azizan, Marco Pavone
2022	J	`jnl`	Control-oriented meta-learning. CoRR Spencer M. Richards, Navid Azizan, Jean-Jacques E. Slotine, Marco Pavone
2022	J	`jnl`	Explicit Regularization via Regularizer Mirror Descent. CoRR Navid Azizan, Sahin Lale, Babak Hassibi
2022	A*	`conf`	Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently. NeurIPS Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis, Navid Azizan
2022	J	`jnl`	Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently. CoRR Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis, Navid Azizan
2022	—	`conf`	One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares. CDC Youngjae Min, Kwangjun Ahn, Navid Azizan
2022	J	`jnl`	One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares. CoRR Youngjae Min, Kwangjun Ahn, Navid Azizan
2022	J	`jnl`	Online Learning for Traffic Routing under Unknown Preferences. CoRR Devansh Jalota, Karthik Gopalakrishnan, Navid Azizan, Ramesh Johari, Marco Pavone
2022	J	`jnl`	Stochastic Mirror Descent on Overparameterized Nonlinear Models. IEEE Trans. Neural Networks Learn. Syst. Navid Azizan, Sahin Lale, Babak Hassibi
2022	J	`jnl`	Uncertainty in Contrastive Learning: On the Predictability of Downstream Performance. CoRR Shervin Ardeshir, Navid Azizan
2022	J	`jnl`	Uncertainty-Aware Meta-Learning for Multimodal Task Distributions. CoRR Cesar Almecija, Apoorva Sharma, Navid Azizan
2021	—	`conf`	Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems. Robotics: Science and Systems Spencer M. Richards, Navid Azizan, Jean-Jacques E. Slotine, Marco Pavone
2021	J	`jnl`	Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems. CoRR Spencer M. Richards, Navid Azizan, Jean-Jacques E. Slotine, Marco Pavone
2021	J	`jnl`	Sketching Curvature for Efficient Out-of-Distribution Detection for Deep Neural Networks. CoRR Apoorva Sharma, Navid Azizan, Marco Pavone
2021	A	`conf`	Sketching curvature for efficient out-of-distribution detection for deep neural networks. UAI Apoorva Sharma, Navid Azizan, Marco Pavone
2020	Misc	`conf`	A Study of Generalization of Stochastic Mirror Descent Algorithms on Overparameterized Nonlinear Models. ICASSP Navid Azizan, Sahin Lale, Babak Hassibi
2020	J	`jnl`	Optimal Pricing in Markets with Nonconvex Costs. Oper. Res. Navid Azizan, Yu Su, Krishnamurthy Dvijotham, Adam Wierman
2020	A	`conf`	Orthogonal Gradient Descent for Continual Learning. AISTATS Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li
2019	—	`conf`	A Stochastic Interpretation of Stochastic Mirror Descent: Risk-Sensitive Optimality. CDC Navid Azizan, Babak Hassibi
2019	J	`jnl`	Optimization Algorithms for Large-Scale Systems: From Deep Learning to Energy Markets. SIGMETRICS Perform. Evaluation Rev. Navid Azizan
2019	J	`jnl`	Orthogonal Gradient Descent for Continual Learning. CoRR Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li