Adel Javanmard

22 papers · 2012–2025 · 5 conferences · across top CS/AI conferences

Achievements

+9 more ↓

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🌍 Conference Polyglot (5)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏆 Keyword Champion (2) 🗃️ Keyword Collector (81) 🚀 Conference Pioneer 💎 Century Club (22) 📈 Trend Setter ⚡ Prolific Year (5)

Conferences

ICML (8) JMLR (5) NIPS (5) COLT (2) ICLR (2)

Top co-authors

Vahab Mirrokni (9) Andrea Montanari (3) Gang Fu (2) Ryan A. Rossi (2) Matthew Fahrbach (2) Jean Pouget-Abadie (2) Lin Chen (2) Sebastien Lahaie (1) Murat A Erdogdu (1) Sungchul Kim (1)

Research topics

Statistics (1)

Keywords

regret bound (5) online learning (4) dynamic pricing (3) high-dimensional regression (3) stochastic gradient descent (2) adversarial training (2) hypothesis testing (2) regret analysis (2) regret minimization (2) confidence interval (2) robust optimization (1) feature selection (1) weakly supervised learning (1) pac learning (1) manifold learning (1) dimensionality reduction (1) empirical risk minimization (1) statistical inference (1) reinforcement learning (1) high-dimensional statistics (1)

Papers

Integer Programming for Generalized Causal Bootstrap Designs ICML 2025 Improving the Variance of Differentially Private Randomized Experiments through Clustering ICML 2025 DeepCrossAttention: Supercharging Transformer Residual Connections ICML 2025 Retraining with Predicted Hard Labels Provably Increases Model Accuracy ICML 2025 Robust Feature Learning for Multi-Index Models in High Dimensions ICLR 2025 PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses ICML 2024 Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions ICLR 2024 Optimistic Rates for Learning from Label Proportions COLT 2024 Structured Dynamic Pricing: Optimal Regret in a Global Shrinkage Model JMLR 2024 Learning Rate Schedules in the Presence of Distribution Shift ICML 2023 Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization NIPS 2023 Fundamental Tradeoffs in Distributionally Adversarial Training ICML 2021 Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning JMLR 2020 Precise Tradeoffs in Adversarial Training for Linear Regression COLT 2020 Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions NIPS 2019 Dynamic Pricing in High-dimensions JMLR 2019 Perishability of Data: Dynamic Pricing under Varying-Coefficient Models JMLR 2017 Confidence Intervals and Hypothesis Testing for High-Dimensional Regression JMLR 2014 Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition NIPS 2013 Learning Linear Bayesian Networks with Latent Variables ICML 2013 Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models NIPS 2013 Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems NIPS 2012