Azizan, Navid

16 publications

NeurIPS 2025 Activation-Informed Merging of Large Language Models Amin Heyrani Nobari, Kaveh Alim, Ali ArjomandBigdeli, Akash Srivastava, Faez Ahmed, Navid Azizan

NeurIPS 2025 Know What You Don't Know: Uncertainty Calibration of Process Reward Models Young-Jin Park, Kristjan Greenewald, Kaveh Alim, Hao Wang, Navid Azizan

L4DC 2025 Meta-Learning for Adaptive Control with Automated Mirror Descent Sunbochen Tang, Haoyuan Sun, Navid Azizan

NeurIPSW 2024 Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection Aaron Alvarado Kristanto Julistiono, Davoud Ataee Tarzanagh, Navid Azizan

NeurIPSW 2024 Probabilistic Forecasting for Building Energy Systems: Are Time-Series Foundation Models the Answer? Young-Jin Park, François Germain, Jing Liu, Ye Wang, Gordon Wichern, Toshiaki Koike-Akino, Navid Azizan, Christopher R. Laughman, Ankush Chakrabarty

UAI 2024 Quantifying Representation Reliability in Self-Supervised Learning Models Young-Jin Park, Hao Wang, Shervin Ardeshir, Navid Azizan

JMLR 2023 A Unified Approach to Controlling Implicit Regularization via Mirror Descent Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan

ICML 2023 Learning Control-Oriented Dynamical Structure from Data Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, Marco Pavone

AISTATS 2023 Online Learning for Traffic Routing Under Unknown Preferences Devansh Jalota, Karthik Gopalakrishnan, Navid Azizan, Ramesh Johari, Marco Pavone

AISTATS 2022 A Unified View of SDP-Based Neural Network Verification Through Completely Positive Programming Robin A. Brown, Edward Schmerling, Navid Azizan, Marco Pavone

NeurIPSW 2022 Embedding Reliability: On the Predictability of Downstream Performance Shervin Ardeshir, Navid Azizan

NeurIPS 2022 Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis, Navid Azizan

NeurIPSW 2022 Uncertainty-Aware Meta-Learning for Multimodal Task Distributions Cesar Almecija, Apoorva Sharma, Young-Jin Park, Navid Azizan

UAI 2021 Sketching Curvature for Efficient Out-of-Distribution Detection for Deep Neural Networks Apoorva Sharma, Navid Azizan, Marco Pavone

AISTATS 2020 Orthogonal Gradient Descent for Continual Learning Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li

ICLR 2019 Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization Navid Azizan, Babak Hassibi