676 citations · 1k across the 35 of their papers we have counts for
10 papers · 1 filter
Structured Dynamic Pricing: Optimal Regret in a Global Shrinkage Model
Rashmi Ranjan Bhuyan, Adel Javanmard, Sungchul Kim +4
We consider dynamic pricing strategies in a streamed longitudinal data set-up where the objective is to maximize, over time, the cumulative profit across a large number of customer…
Learning Rate Schedules in the Presence of Distribution Shift
Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni +1
We design learning rate schedules that minimize regret for SGD-based online learning in the presence of a changing data distribution. We fully characterize the optimal learning rat…
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression
Hamed Hassani, Adel Javanmard
Successful deep learning models often involve training neural network architectures that contain more parameters than the number of training samples. Such overparametrized models h…
Adversarial robustness for latent models: Revisiting the robust-standard accuracies tradeoff
Adel Javanmard, Mohammad Mehrabi
Over the past few years, several adversarial training methods have been proposed to improve the robustness of machine learning models against adversarial perturbations in the input…
Fundamental Tradeoffs in Distributionally Adversarial Training
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi +2
Adversarial training is among the most effective techniques to improve the robustness of models against adversarial perturbations. However, the full effect of this approach on mode…
Dynamic Incentive-aware Learning: Robust Pricing in Contextual Auctions
Negin Golrezaei, Adel Javanmard, Vahab Mirrokni
Motivated by pricing in ad exchange markets, we consider the problem of robust learning of reserve prices against strategic buyers in repeated contextual second-price auctions. Buy…