activity
20172025
most citedSynthetic Data Applications in Finance

8 citations · 24 across the 16 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.LG2022

Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe

Renbo Zhao, Niccolò Dalmasso, Mohsen Ghassemi +3

Hawkes processes have recently risen to the forefront of tools when it comes to modeling and generating sequential events data. Multidimensional Hawkes processes model both the sel…

stat.ML2022★ 2 cited

Online Learning for Mixture of Multivariate Hawkes Processes

Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba +4

Online learning of Hawkes processes has received increasing attention in the last couple of years especially for modeling a network of actors. However, these works typically either…

stat.ML2022

Differentially Private Learning of Hawkes Processes

Mohsen Ghassemi, Eleonora Kreačić, Niccolò Dalmasso +3

Hawkes processes have recently gained increasing attention from the machine learning community for their versatility in modeling event sequence data. While they have a rich history…

stat.AP2022★ 8 cited

Structural Forecasting for Short-term Tropical Cyclone Intensity Guidance

Trey McNeely, Pavel Khokhlov, Niccolo Dalmasso +2

Because geostationary satellite (Geo) imagery provides a high temporal resolution window into tropical cyclone (TC) behavior, we investigate the viability of its application to sho…

stat.ML2022★ 3 cited

Fair When Trained, Unfair When Deployed: Observable Fairness Measures are Unstable in Performative Prediction Settings

Alan Mishler, Niccolò Dalmasso

Many popular algorithmic fairness measures depend on the joint distribution of predictions, outcomes, and a sensitive feature like race or gender. These measures are sensitive to d…