Javanmard, Adel

26 publications

ICLR 2026 Understanding the Role of Training Data in Test-Time Scaling Adel Javanmard, Baharan Mirzasoleiman, Vahab Mirrokni

ICML 2025 DeepCrossAttention: Supercharging Transformer Residual Connections Mike Heddes, Adel Javanmard, Kyriakos Axiotis, Gang Fu, Mohammadhossein Bateni, Vahab Mirrokni

ICML 2025 Improving the Variance of Differentially Private Randomized Experiments Through Clustering Adel Javanmard, Vahab Mirrokni, Jean Pouget-Abadie

ICML 2025 Integer Programming for Generalized Causal Bootstrap Designs Jennifer Rogers Brennan, Sebastien Lahaie, Adel Javanmard, Nick Doudchenko, Jean Pouget-Abadie

ICML 2025 Retraining with Predicted Hard Labels Provably Increases Model Accuracy Rudrajit Das, Inderjit S Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong

ICLR 2025 Robust Feature Learning for Multi-Index Models in High Dimensions Alireza Mousavi-Hosseini, Adel Javanmard, Murat A Erdogdu

NeurIPS 2025 Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing Adel Javanmard, Rudrajit Das, Alessandro Epasto, Vahab Mirrokni

ICLR 2024 Learning from Aggregate Responses: Instance Level Versus Bag Level Loss Functions Adel Javanmard, Lin Chen, Vahab Mirrokni, Ashwinkumar Badanidiyuru, Gang Fu

COLT 2024 Optimistic Rates for Learning from Label Proportions Gene Li, Lin Chen, Adel Javanmard, Vahab Mirrokni

ICML 2024 PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni

NeurIPSW 2024 Robust Feature Learning for Multi-Index Models in High Dimensions Alireza Mousavi-Hosseini, Adel Javanmard, Murat A Erdogdu

JMLR 2024 Structured Dynamic Pricing: Optimal Regret in a Global Shrinkage Model Rashmi Ranjan Bhuyan, Adel Javanmard, Sungchul Kim, Gourab Mukherjee, Ryan A. Rossi, Tong Yu, Handong Zhao

NeurIPSW 2023 A New Framework for Measuring Re-Identification Risk Cj Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andres Munoz Medina, Vahab Mirrokni, Gabriel Nunes, Sergei Vassilvitskii, Peilin Zhong

NeurIPS 2023 Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization Adel Javanmard, Vahab Mirrokni

ICML 2023 Learning Rate Schedules in the Presence of Distribution Shift Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah

ICML 2021 Fundamental Tradeoffs in Distributionally Adversarial Training Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai

JMLR 2020 Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning Ery Arias-Castro, Adel Javanmard, Bruno Pelletier

COLT 2020 Precise Tradeoffs in Adversarial Training for Linear Regression Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani

NeurIPS 2019 Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions Negin Golrezaei, Adel Javanmard, Vahab Mirrokni

JMLR 2019 Dynamic Pricing in High-Dimensions Adel Javanmard, Hamid Nazerzadeh

JMLR 2017 Perishability of Data: Dynamic Pricing Under Varying-Coefficient Models Adel Javanmard

JMLR 2014 Confidence Intervals and Hypothesis Testing for High-Dimensional Regression Adel Javanmard, Andrea Montanari

NeurIPS 2013 Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models Adel Javanmard, Andrea Montanari

ICML 2013 Learning Linear Bayesian Networks with Latent Variables Animashree Anandkumar, Daniel Hsu, Adel Javanmard, Sham Kakade

NeurIPS 2013 Model Selection for High-Dimensional Regression Under the Generalized Irrepresentability Condition Adel Javanmard, Andrea Montanari

NeurIPS 2012 Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems Morteza Ibrahimi, Adel Javanmard, Benjamin V. Roy