2 citations · 2 across the 2 of their papers we have counts for
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cs.LG2023
From Stream to Pool: Pricing Under the Law of Diminishing Marginal Utility
Titing Cui, Su Jia, Thomas Lavastida
Dynamic pricing models often posit that a of customer interactions occur sequentially, where customers' valuations are drawn independently. However, this model is…
cs.LG2022★ 2 cited
Algorithms with Prediction Portfolios
Michael Dinitz, Sungjin Im, Thomas Lavastida +2
The research area of algorithms with predictions has seen recent success showing how to incorporate machine learning into algorithm design to improve performance when the predictio…
cs.LG2020
Learnable and Instance-Robust Predictions for Online Matching, Flows and Load Balancing
Thomas Lavastida, Benjamin Moseley, R. Ravi +1
We propose a new model for augmenting algorithms with predictions by requiring that they are formally learnable and instance robust. Learnability ensures that predictions can be ef…