15 citations · 48 across the 32 of their papers we have counts for
5 papers · 1 filter
Beyond Linear Diffusions: Improved Representations for Rare Conditional Generative Modeling
Kulunu Dharmakeerthi, Yousef El-Laham, Henry H. Wong +3
Diffusion models have emerged as powerful generative frameworks with widespread applications across machine learning and artificial intelligence systems. While current research has…
Fair Wasserstein Coresets
Zikai Xiong, Niccolò Dalmasso, Shubham Sharma +5
Data distillation and coresets have emerged as popular approaches to generate a smaller representative set of samples for downstream learning tasks to handle large-scale datasets.…
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…
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…
Conservative Exploration using Interleaving
Sumeet Katariya, Branislav Kveton, Zheng Wen +1
In many practical problems, a learning agent may want to learn the best action in hindsight without ever taking a bad action, which is significantly worse than the default producti…