37 citations · 78 across the 12 of their papers we have counts for
13 papers
Sample Average Approximation for Black-Box VI
Javier Burroni, Justin Domke, Daniel Sheldon
We present a novel approach for black-box VI that bypasses the difficulties of stochastic gradient ascent, including the task of selecting step-sizes. Our approach involves using a…
U-Statistics for Importance-Weighted Variational Inference
Javier Burroni, Kenta Takatsu, Justin Domke +1
We propose the use of U-statistics to reduce variance for gradient estimation in importance-weighted variational inference. The key observation is that, given a base gradient estim…
Automatically Marginalized MCMC in Probabilistic Programming
Jinlin Lai, Javier Burroni, Hui Guan +1
Hamiltonian Monte Carlo (HMC) is a powerful algorithm to sample latent variables from Bayesian models. The advent of probabilistic programming languages (PPLs) frees users from wri…
The Random Conditional Distribution for Higher-Order Probabilistic Inference
Zenna Tavares, Xin Zhang, Edgar Minaysan +3
The need to condition distributional properties such as expectation, variance, and entropy arises in algorithmic fairness, model simplification, robustness and many other areas. At…
Soft Constraints for Inference with Declarative Knowledge
Zenna Tavares, Javier Burroni, Edgar Minaysan +2
We develop a likelihood free inference procedure for conditioning a probabilistic model on a predicate. A predicate is a Boolean valued function which expresses a yes/no question a…
Inference of Demographic Attributes based on Mobile Phone Usage Patterns and Social Network Topology
Carlos Sarraute, Jorge Brea, Javier Burroni +1
Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper, we focus on the population of…
Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming
Guillaume Baudart, Javier Burroni, Martin Hirzel +2
Stan is a probabilistic programming language that is popular in the statistics community, with a high-level syntax for expressing probabilistic models. Stan differs by nature from…
Inference of Users Demographic Attributes based on Homophily in Communication Networks
Jorge Brea, Javier Burroni, Carlos Sarraute
Over the past decade, mobile phones have become prevalent in all parts of the world, across all demographic backgrounds. Mobile phones are used by men and women across a wide age r…
Social Events in a Time-Varying Mobile Phone Graph
Carlos Sarraute, Jorge Brea, Javier Burroni +3
The large-scale study of human mobility has been significantly enhanced over the last decade by the massive use of mobile phones in urban populations. Studying the activity of mobi…
Harnessing Mobile Phone Social Network Topology to Infer Users Demographic Attributes
Jorge Brea, Javier Burroni, Martin Minnoni +1
We study the structure of the social graph of mobile phone users in the country of Mexico, with a focus on demographic attributes of the users (more specifically the users' age). W…
A Study of Age and Gender seen through Mobile Phone Usage Patterns in Mexico
Carlos Sarraute, Pablo Blanc, Javier Burroni
Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of M…
Outrepasser les limites des techniques classiques de Prise d'Empreintes grace aux Reseaux de Neurones
Javier Burroni, Carlos Sarraute
We present an application of Artificial Intelligence techniques to the field of Information Security. The problem of remote Operating System (OS) Detection, also called OS Fingerpr…
Using Neural Networks to improve classical Operating System Fingerprinting techniques
Carlos Sarraute, Javier Burroni
We present remote Operating System detection as an inference problem: given a set of observations (the target host responses to a set of tests), we want to infer the OS type which…