4 papers
Score-based Metropolis-Hastings for Fractional Langevin Algorithms
Ahmed Aloui, Junyi Liao, Ali Hasan +2
Sampling from heavy-tailed and multimodal distributions is challenging when neither the target density nor the proposal density can be evaluated, as in -stable Lévy-driven fra…
Elliptic Loss Regularization
Ali Hasan, Haoming Yang, Yuting Ng +1
Regularizing neural networks is important for anticipating model behavior in regions of the data space that are not well represented. In this work, we propose a regularization tech…
Parabolic Continual Learning
Haoming Yang, Ali Hasan, Vahid Tarokh
Regularizing continual learning techniques is important for anticipating algorithmic behavior under new realizations of data. We introduce a new approach to continual learning by i…
Indiscriminate Disruption of Conditional Inference on Multivariate Gaussians
William N. Caballero, Matthew LaRosa, Alexander Fisher +1
The multivariate Gaussian distribution underpins myriad operations-research, decision-analytic, and machine-learning models (e.g., Bayesian optimization, Gaussian influence diagram…