Adel Javanmard

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 46

Top Topics

False Discovery Rate

Hypothesis Testing

Causal Inference

Dynamic Pricing

Top Venues

J. Mach. Learn. Res.

IEEE Trans. Inf. Theory

Publications

Gene Li, Lin Chen, Adel Javanmard, Vahab Mirrokni
Optimistic Rates for Learning from Label Proportions. CoRR (2024)
Adel Javanmard, Lin Chen, Vahab Mirrokni, Ashwinkumar Badanidiyuru, Gang Fu
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions. CoRR (2024)
Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong
Retraining with Predicted Hard Labels Provably Increases Model Accuracy. CoRR (2024)
Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses. CoRR (2024)
Adel Javanmard, Mohammad Mehrabi
Adversarial Robustness for Latent Models: Revisiting the Robust-Standard Accuracies Tradeoff. Oper. Res. 72 (3) (2024)
Adel Javanmard, Lin Chen, Vahab Mirrokni, Ashwinkumar Badanidiyuru, Gang Fu
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions. ICLR (2024)
Gene Li, Lin Chen, Adel Javanmard, Vahab Mirrokni
Optimistic Rates for Learning from Label Proportions. COLT (2024)
Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah
Learning Rate Schedules in the Presence of Distribution Shift. CoRR (2023)
Adel Javanmard, Vahab Mirrokni
Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization. NeurIPS (2023)
Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah
Learning Rate Schedules in the Presence of Distribution Shift. ICML (2023)
CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andres Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong
Measuring Re-identification Risk. Proc. ACM Manag. Data 1 (2) (2023)
CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andrés Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong
Measuring Re-identification Risk. CoRR (2023)
Rashmi Ranjan Bhuyan, Adel Javanmard, Sungchul Kim, Gourab Mukherjee, Ryan A. Rossi, Tong Yu, Handong Zhao
Structured Dynamic Pricing: Optimal Regret in a Global Shrinkage Model. CoRR (2023)
Adel Javanmard, Vahab Mirrokni
Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization. CoRR (2023)
Adel Javanmard, Vahab Mirrokni, Jean Pouget-Abadie
Causal Inference with Differentially Private (Clustered) Outcomes. CoRR (2023)
Hamed Hassani, Adel Javanmard
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression. CoRR (2022)
Adel Javanmard, Mohammad Mehrabi
GRASP: A Goodness-of-Fit Test for Classification Learning. CoRR (2022)
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai
Fundamental Tradeoffs in Distributionally Adversarial Training. CoRR (2021)
Adel Javanmard, Mohammad Mehrabi
Adversarial robustness for latent models: Revisiting the robust-standard accuracies tradeoff. CoRR (2021)
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup B. Rao, Tung Mai
Fundamental Tradeoffs in Distributionally Adversarial Training. ICML (2021)
Negin Golrezaei, Adel Javanmard, Vahab S. Mirrokni
Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions. Oper. Res. 69 (1) (2021)
Simeng Shao, Jacob Bien, Adel Javanmard
Controlling the False Split Rate in Tree-Based Aggregation. CoRR (2021)
Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani
Precise Tradeoffs in Adversarial Training for Linear Regression. CoRR (2020)
Negin Golrezaei, Adel Javanmard, Vahab S. Mirrokni
Dynamic Incentive-aware Learning: Robust Pricing in Contextual Auctions. CoRR (2020)
Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani
Precise Tradeoffs in Adversarial Training for Linear Regression. COLT (2020)
Adel Javanmard, Hamid Nazerzadeh, Simeng Shao
Multi-Product Dynamic Pricing in High-Dimensions with Heterogeneous Price Sensitivity. ISIT (2020)
Ery Arias-Castro, Adel Javanmard, Bruno Pelletier
Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning. J. Mach. Learn. Res. 21 (2020)
Adel Javanmard, Mahdi Soltanolkotabi
Precise Statistical Analysis of Classification Accuracies for Adversarial Training. CoRR (2020)
Mahdi Soltanolkotabi, Adel Javanmard, Jason D. Lee
Theoretical Insights Into the Optimization Landscape of Over-Parameterized Shallow Neural Networks. IEEE Trans. Inf. Theory 65 (2) (2019)
David S. Robertson, Jan Wildenhain, Adel Javanmard, Natasha A. Karp
onlineFDR: an R package to control the false discovery rate for growing data repositories. Bioinform. 35 (20) (2019)
Adel Javanmard, Hamid Nazerzadeh
Dynamic Pricing in High-dimensions. J. Mach. Learn. Res. 20 (2019)
Adel Javanmard, Hamid Nazerzadeh, Simeng Shao
Multi-Product Dynamic Pricing in High-Dimensions with Heterogenous Price Sensitivity. CoRR (2019)
Adel Javanmard, Marco Mondelli, Andrea Montanari
Analysis of a Two-Layer Neural Network via Displacement Convexity. CoRR (2019)
Yash Deshpande, Adel Javanmard, Mohammad Mehrabi
Online Debiasing for Adaptively Collected High-dimensional Data. CoRR (2019)
Amin Jalali, Adel Javanmard, Maryam Fazel
New Computational and Statistical Aspects of Regularized Regression with Application to Rare Feature Selection and Aggregation. CoRR (2019)
Negin Golrezaei, Adel Javanmard, Vahab S. Mirrokni
Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions. NeurIPS (2019)
Ery Arias-Castro, Adel Javanmard, Bruno Pelletier
Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning. CoRR (2018)
Adel Javanmard, Hamid Javadi
False Discovery Rate Control via Debiased Lasso. CoRR (2018)
Adel Javanmard
Perishability of Data: Dynamic Pricing under Varying-Coefficient Models. J. Mach. Learn. Res. 18 (2017)
Anand Bhaskar, Adel Javanmard, Thomas A. Courtade, David Tse
Novel probabilistic models of spatial genetic ancestry with applications to stratification correction in genome-wide association studies. Bioinform. 33 (6) (2017)
Mahdi Soltanolkotabi, Adel Javanmard, Jason D. Lee
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks. CoRR (2017)
Adel Javanmard
Perishability of Data: Dynamic Pricing under Varying-Coefficient Models. CoRR (2017)
Adel Javanmard, Jason D. Lee
A Flexible Framework for Hypothesis Testing in High-dimensions. CoRR (2017)
Adel Javanmard, Andrea Montanari, Federico Ricci-Tersenghi
Performance of a community detection algorithm based on semidefinite programming. CoRR (2016)
Adel Javanmard, Andrea Montanari
Online Rules for Control of False Discovery Rate and False Discovery Exceedance. CoRR (2016)
Adel Javanmard, Hamid Nazerzadeh
Dynamic Pricing in High-dimensions. CoRR (2016)
Adel Javanmard, Andrea Montanari, Federico Ricci-Tersenghi
Phase Transitions in Semidefinite Relaxations. CoRR (2015)
Adel Javanmard, Andrea Montanari
On Online Control of False Discovery Rate. CoRR (2015)
Saieed Akbari, Akbar Daemi, Omid Hatami, Adel Javanmard, Abbas Mehrabian
Nowhere-zero Unoriented Flows in Hamiltonian Graphs. Ars Comb. 120 (2015)
Sonia A. Bhaskar, Adel Javanmard
1-bit matrix completion under exact low-rank constraint. CISS (2015)
Adel Javanmard, Andrea Montanari
Hypothesis Testing in High-Dimensional Regression Under the Gaussian Random Design Model: Asymptotic Theory. IEEE Trans. Inf. Theory 60 (10) (2014)
Adel Javanmard, Andrea Montanari
Confidence intervals and hypothesis testing for high-dimensional regression. J. Mach. Learn. Res. 15 (1) (2014)
Adel Javanmard, Andrea Montanari
Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition. NIPS (2013)
Adel Javanmard, Andrea Montanari
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory CoRR (2013)
Animashree Anandkumar, Daniel J. Hsu, Adel Javanmard, Sham M. Kakade
Learning Linear Bayesian Networks with Latent Variables. ICML (1) (2013)
Adel Javanmard, Andrea Montanari
Confidence Intervals and Hypothesis Testing for High-Dimensional Regression. CoRR (2013)
David L. Donoho, Adel Javanmard, Andrea Montanari
Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing. IEEE Trans. Inf. Theory 59 (11) (2013)
Adel Javanmard, Andrea Montanari
Nearly Optimal Sample Size in Hypothesis Testing for High-Dimensional Regression. CoRR (2013)
Adel Javanmard, Andrea Montanari
Localization from Incomplete Noisy Distance Measurements. Found. Comput. Math. 13 (3) (2013)
Adel Javanmard, Andrea Montanari
Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition CoRR (2013)
Morteza Ibrahimi, Adel Javanmard, Benjamin Van Roy
Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems CoRR (2013)
Adel Javanmard, Andrea Montanari
Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models. NIPS (2013)
Adel Javanmard, Andrea Montanari
Nearly optimal sample size in hypothesis testing for high-dimensional regression. Allerton (2013)
Adel Javanmard, Andrea Montanari
Subsampling at information theoretically optimal rates. ISIT (2012)
Adel Javanmard, Maya Haridasan, Li Zhang
Multi-track map matching. SIGSPATIAL/GIS (2012)
Adel Javanmard, Maya Haridasan, Li Zhang
Poster: multi-track map matching. MobiSys (2012)
Adel Javanmard, Andrea Montanari
Subsampling at Information Theoretically Optimal Rates CoRR (2012)
Adel Javanmard, Li Zhang
The minimax risk of truncated series estimators for symmetric convex polytopes CoRR (2012)
Adel Javanmard, Andrea Montanari
State Evolution for General Approximate Message Passing Algorithms, with Applications to Spatial Coupling CoRR (2012)
Animashree Anandkumar, Daniel J. Hsu, Adel Javanmard, Sham M. Kakade
Learning Linear Bayesian Networks with Latent Variables CoRR (2012)
Adel Javanmard, Li Zhang
The minimax risk of truncated series estimators for symmetric convex polytopes. ISIT (2012)
Mohammad Alizadeh, Adel Javanmard, Shang-Tse Chuang, Sundar Iyer, Yi Lu
Versatile refresh: low complexity refresh scheduling for high-throughput multi-banked eDRAM. SIGMETRICS (2012)
David L. Donoho, Adel Javanmard, Andrea Montanari
Information-theoretically optimal compressed sensing via spatial coupling and approximate message passing. ISIT (2012)
Adel Javanmard, Maya Haridasan, Li Zhang
Multi-track Map Matching CoRR (2012)
Morteza Ibrahimi, Adel Javanmard, Benjamin Van Roy
Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems. NIPS (2012)
Morteza Ibrahimi, Adel Javanmard, Yashodhan Kanoria, Andrea Montanari
Robust max-product belief propagation. ACSCC (2011)
Mohammad Alizadeh, Adel Javanmard, Balaji Prabhakar
Analysis of DCTCP: stability, convergence, and fairness. SIGMETRICS (2011)
David L. Donoho, Adel Javanmard, Andrea Montanari
Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing CoRR (2011)
Adel Javanmard, Andrea Montanari
Localization from incomplete noisy distance measurements. ISIT (2011)
Adel Javanmard, Andrea Montanari
Localization from Incomplete Noisy Distance Measurements CoRR (2011)
Morteza Ibrahimi, Adel Javanmard, Yashodhan Kanoria, Andrea Montanari
Robust Max-Product Belief Propagation CoRR (2011)
Saieed Akbari, Akbar Daemi, Omid Hatami, Adel Javanmard, Abbas Mehrabian
Zero-Sum Flows in Regular Graphs. Graphs Comb. 26 (5) (2010)
Adel Javanmard, Farid Ashtiani
Analytical evaluation of average delay and maximum stable throughput along a typical two-way street for vehicular ad hoc networks in sparse situations. Comput. Commun. 32 (16) (2009)
G. Hosein Mohimani, Farid Ashtiani, Adel Javanmard, Maziyar Hamdi
Mobility Modeling, Spatial Traffic Distribution, and Probability of Connectivity for Sparse and Dense Vehicular Ad Hoc Networks. IEEE Trans. Veh. Technol. 58 (4) (2009)
Adel Javanmard, P. Pad, Massoud Babaie-Zadeh, Christian Jutten
Estimating the mixing matrix in underdetermined Sparse Component Analysis (SCA) using consecutive independent component analysis (ICA). EUSIPCO (2008)