Niccolò Dalmasso

29 papers A* 5A 4Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Auditing and Enforcing Conditional Fairness via Optimal Transport. AAAI Mohsen Ghassemi, Alan Mishler, Niccolò Dalmasso, Luhao Zhang, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2025	A	`conf`	Mixup Regularization: A Probabilistic Perspective. UAI Yousef El-Laham, Niccolò Dalmasso, Svitlana Vyetrenko, Vamsi K. Potluru, Manuela Veloso
2025	J	`jnl`	Mixup Regularization: A Probabilistic Perspective. CoRR Yousef El-Laham, Niccolò Dalmasso, Svitlana Vyetrenko, Vamsi K. Potluru, Manuela Veloso
2025	J	`jnl`	Monty Hall and Optimized Conformal Prediction to Improve Decision-Making with LLMs. CoRR Harit Vishwakarma, Alan Mishler, Thomas Cook, Niccolò Dalmasso, Natraj Raman, Sumitra Ganesh
2025	A*	`conf`	Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction. ICML Harit Vishwakarma, Alan Mishler, Thomas Cook, Niccolò Dalmasso, Natraj Raman, Sumitra Ganesh
2025	J	`jnl`	Toward Breaking Watermarks in Distortion-free Large Language Models. CoRR Shayleen Reynolds, Saheed Obitayo, Niccolò Dalmasso, Dung Daniel T. Ngo, Vamsi K. Potluru, Manuela Veloso
2024	J	`jnl`	Auditing and Enforcing Conditional Fairness via Optimal Transport. CoRR Mohsen Ghassemi, Alan Mishler, Niccolò Dalmasso, Luhao Zhang, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2024	A*	`conf`	Fair Wasserstein Coresets. NeurIPS Zikai Xiong, Niccolò Dalmasso, Shubham Sharma, Freddy Lécué, Daniele Magazzeni, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2024	A*	`conf`	FairWASP: Fast and Optimal Fair Wasserstein Pre-processing. AAAI Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2024	J	`jnl`	Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic. Trans. Mach. Learn. Res. Matteo Sordello, Niccolò Dalmasso, Hangfeng He, Weijie J. Su
2024	J	`jnl`	Synthetic Data Applications in Finance. CoRR Vamsi K. Potluru, Daniel Borrajo, Andrea Coletta, Niccolò Dalmasso, Yousef El-Laham, Elizabeth Fons, Mohsen Ghassemi, Sriram Gopalakrishnan, Vikesh Gosai, Eleonora Kreacic, Ganapathy Mani, Saheed Obitayo, Deepak Paramanand, Natraj Raman, Mikhail Solonin, Srijan Sood, Svitlana Vyetrenko, Haibei Zhu, Manuela Veloso, Tucker Balch
2023	J	`jnl`	Deep Gaussian Mixture Ensembles. CoRR Yousef El-Laham, Niccolò Dalmasso, Elizabeth Fons, Svitlana Vyetrenko
2023	A	`conf`	Deep Gaussian mixture ensembles. UAI Yousef El-Laham, Niccolò Dalmasso, Elizabeth Fons, Svitlana Vyetrenko
2023	—	`conf`	Efficient Event Series Data Modeling via First-Order Constrained Optimization. ICAIF Niccolò Dalmasso, Renbo Zhao, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2023	J	`jnl`	Fair Wasserstein Coresets. CoRR Zikai Xiong, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2023	J	`jnl`	FairWASP: Fast and Optimal Fair Wasserstein Pre-processing. CoRR Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2022	J	`jnl`	Differentially Private Learning of Hawkes Processes. CoRR Mohsen Ghassemi, Eleonora Kreacic, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2022	J	`jnl`	Explicit Group Sparse Projection with Applications to Deep Learning and NMF. Trans. Mach. Learn. Res. Riyasat Ohib, Nicolas Gillis, Niccolò Dalmasso, Sameena Shah, Vamsi K. Potluru, Sergey M. Plis
2022	J	`jnl`	Fair When Trained, Unfair When Deployed: Observable Fairness Measures are Unstable in Performative Prediction Settings. CoRR Alan Mishler, Niccolò Dalmasso
2022	J	`jnl`	Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe. CoRR Renbo Zhao, Niccolò Dalmasso, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
2022	—	`conf`	Online Learning for Mixture of Multivariate Hawkes Processes. ICAIF Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Tucker Balch, Sameena Shah, Manuela Veloso
2022	J	`jnl`	Online Learning for Mixture of Multivariate Hawkes Processes. CoRR Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Sameena Shah, Tucker Balch, Manuela Veloso
2021	A	`conf`	Diagnostics for conditional density models and Bayesian inference algorithms. UAI David Zhao, Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee
2021	J	`jnl`	Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning in Simulation and Uncertainty Quantification. CoRR Niccolò Dalmasso, David Zhao, Rafael Izbicki, Ann B. Lee
2020	J	`jnl`	Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference. Astron. Comput. Niccolò Dalmasso, Taylor Pospisil, Ann B. Lee, Rafael Izbicki, Peter E. Freeman, Alex I. Malz
2020	A*	`conf`	Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting. ICML Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee
2020	J	`jnl`	Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting. CoRR Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee
2020	J	`jnl`	Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning. CoRR Trey McNeely, Niccolò Dalmasso, Kimberly M. Wood, Ann B. Lee
2020	A	`conf`	Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations. AISTATS Niccolò Dalmasso, Ann B. Lee, Rafael Izbicki, Taylor Pospisil, Ilmun Kim, Chieh-An Lin