Thomas Lavastida

According to our database, Thomas Lavastida authored at least 10 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Controlling Tail Risk in Online Ski-Rental.

Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

2023

From Stream to Pool: Dynamic Pricing Beyond i.i.d. Arrivals.

Titing Cui, Su Jia, Thomas Lavastida

CoRR, 2023

2022

Algorithms with Prediction Portfolios.

Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Faster Matchings via Learned Duals.

Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Scalable Approximation Algorithm for Weighted Longest Common Subsequence.

Jeremy Buhler, Thomas Lavastida, Kefu Lu, Benjamin Moseley

Proceedings of the Euro-Par 2021: Parallel Processing, 2021

Learnable and Instance-Robust Predictions for Online Matching, Flows and Load Balancing.

Thomas Lavastida, Benjamin Moseley, R. Ravi, Chenyang Xu

Proceedings of the 29th Annual European Symposium on Algorithms, 2021

Scaling Average-Linkage via Sparse Cluster Embeddings.

Thomas Lavastida, Kefu Lu, Benjamin Moseley, Yuyan Wang

Proceedings of the Asian Conference on Machine Learning, 2021

Using Predicted Weights for Ad Delivery.

Thomas Lavastida, Benjamin Moseley, R. Ravi, Chenyang Xu

Proceedings of the 2021 SIAM Conference on Applied and Computational Discrete Algorithms, 2021

2020

Online Scheduling via Learned Weights.

Silvio Lattanzi, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

2019

A Framework for Parallelizing Hierarchical Clustering Methods.

Silvio Lattanzi, Thomas Lavastida, Kefu Lu, Benjamin Moseley

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019