2 citations · 2 across the 4 of their papers we have counts for
5 papers
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…
Controlling Tail Risk in Online Ski-Rental
Michael Dinitz, Sungjin Im, Thomas Lavastida +2
The classical ski-rental problem admits a textbook 2-competitive deterministic algorithm, and a simple randomized algorithm that is -competitive in expectation. The…
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…
Using Predicted Weights for Ad Delivery
Thomas Lavastida, Benjamin Moseley, R. Ravi +1
We study the performance of a proportional weights algorithm for online capacitated bipartite matching modeling the delivery of impression ads. The algorithm uses predictions on th…
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…