Directed Networks
Learning Hawkes Processes from a handful of events
Farnood Salehi, William Trouleau, Matthias Grossglauser, Patrick Thiran
Neural Information Processing Systems http://nips.cc/
Demystifying the Optimal Performance of Multi-Class Classification
Inspired by the work by Ishida et al. (2023), we propose an estimator
From Stochastic Planning to Marginal MAP
Hao(Jackson) Cui, Radu Marinescu, Roni Khardon
Neural Information Processing Systems http://nips.cc/
Learning Concave Conditional Likelihood Models for Improved Analysis of Tandem Mass Spectra
John T. Halloran, David M. Rocke
The most widely used technology to identify the proteins present in a complex biological sample istandem mass spectrometry,which quickly produces alarge collection of spectra representative of thepeptides (i.e., protein subsequences) present in the original sample.
Maximizing acquisition functions for Bayesian optimization
James Wilson, Frank Hutter, Marc Deisenroth
Neural Information Processing Systems http://nips.cc/
Robust Learning of Fixed-Structure Bayesian Networks
Yu Cheng, Ilias Diakonikolas, Daniel Kane, Alistair Stewart
Neural Information Processing Systems http://nips.cc/
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Zi Wang, Beomjoon Kim, Leslie Pack Kaelbling
Neural Information Processing Systems http://nips.cc/