7 citations · 16 across the 10 of their papers we have counts for
4 papers · 1 filter
Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference
Vyacheslav Kungurtsev, Apaar, Aarya Khandelwal +3
In this work, we demonstrate the Empirical Bayes approach to learning a Dynamic Bayesian Network. By starting with several point estimates of structure and weights, we can use a da…
Scaling the Wild: Decentralizing Hogwild!-style Shared-memory SGD
Bapi Chatterjee, Vyacheslav Kungurtsev, Dan Alistarh
Powered by the simplicity of lock-free asynchrony, Hogwilld! is a go-to approach to parallelize SGD over a shared-memory setting. Despite its popularity and concomitant extensions,…
Stochastic Gradient Langevin with Delayed Gradients
Vyacheslav Kungurtsev, Bapi Chatterjee, Dan Alistarh
Stochastic Gradient Langevin Dynamics (SGLD) ensures strong guarantees with regards to convergence in measure for sampling log-concave posterior distributions by adding noise to st…
Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent
Giorgi Nadiradze, Ilia Markov, Bapi Chatterjee +2
Machine learning has made tremendous progress in recent years, with models matching or even surpassing humans on a series of specialized tasks. One key element behind the progress…