221 citations · 572 across the 8 of their papers we have counts for
4 papers · 1 filter
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions
Amar Shah, Zoubin Ghahramani
We develop parallel predictive entropy search (PPES), a novel algorithm for Bayesian optimization of expensive black-box objective functions. At each iteration, PPES aims to select…
Unitary Evolution Recurrent Neural Networks
Martin Arjovsky, Amar Shah, Yoshua Bengio
Recurrent neural networks (RNNs) are notoriously difficult to train. When the eigenvalues of the hidden to hidden weight matrix deviate from absolute value 1, optimization becomes…
Predictive Entropy Search for Multi-objective Bayesian Optimization
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Amar Shah +1
We present PESMO, a Bayesian method for identifying the Pareto set of multi-objective optimization problems, when the functions are expensive to evaluate. The central idea of PESMO…
An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process
Amar Shah, David A. Knowles, Zoubin Ghahramani
Stochastic variational inference (SVI) is emerging as the most promising candidate for scaling inference in Bayesian probabilistic models to large datasets. However, the performanc…