ML Anthology

Dalmasso, Niccolo

15 publications

AAAI 2025 Auditing and Enforcing Conditional Fairness via Optimal Transport Mohsen Ghassemi, Alan Mishler, Niccolò Dalmasso, Luhao Zhang, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
UAI 2025 Mixup Regularization: A Probabilistic Perspective Yousef El-Laham, Niccolo Dalmasso, Svitlana Vyetrenko, Vamsi K. Potluru, Manuela Veloso
ICLRW 2025 Prune 'n Predict: Optimizing LLM Decision-Making with Conformal Prediction Harit Vishwakarma, Thomas Cook, Alan Mishler, Niccolo Dalmasso, Natraj Raman, Sumitra Ganesh
ICML 2025 Prune ’n Predict: Optimizing LLM Decision-Making with Conformal Prediction Harit Vishwakarma, Alan Mishler, Thomas Cook, Niccolo Dalmasso, Natraj Raman, Sumitra Ganesh
NeurIPS 2024 Fair Wasserstein Coresets Zikai Xiong, Niccolò Dalmasso, Shubham Sharma, Freddy Lecue, Daniele Magazzeni, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
AAAI 2024 FairWASP: Fast and Optimal Fair Wasserstein Pre-Processing Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
NeurIPSW 2024 Improving Decision-Making in Open-World Agents with Conformal Prediction and Monty Hall Harit Vishwakarma, Alan Mishler, Thomas Cook, Niccolo Dalmasso, Natraj Raman, Sumitra Ganesh
TMLR 2024 Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic Matteo Sordello, Niccolo Dalmasso, Hangfeng He, Weijie J Su
UAI 2023 Deep Gaussian Mixture Ensembles Yousef El-Laham, Niccolo Dalmasso, Elizabeth Fons, Svitlana Vyetrenko
NeurIPSW 2023 Fair Wasserstein Coresets Zikai Xiong, Niccolo Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
TMLR 2022 Explicit Group Sparse Projection with Applications to Deep Learning and NMF Riyasat Ohib, Nicolas Gillis, Niccolo Dalmasso, Sameena Shah, Vamsi K. Potluru, Sergey Plis
NeurIPSW 2022 Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe Renbo Zhao, Niccolo Dalmasso, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
UAI 2021 Diagnostics for Conditional Density Models and Bayesian Inference Algorithms David Zhao, Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee
ICML 2020 Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting Niccolo Dalmasso, Rafael Izbicki, Ann Lee
AISTATS 2020 Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations Niccolo Dalmasso, Ann Lee, Rafael Izbicki, Taylor Pospisil, Ilmun Kim, Chieh-An Lin