Sub-Linear Debugging

I have a post on sub-linear debugging on Microsoft’s machine learning blog. Online learning algorithms are a class of machine learning (ML) techniques that consume the input as a stream and adapt as they consume input. They are often used for their computational desirability, e.g., for speed, the ability to consume large data sets, and the ability to handle non-convex…
Original post: Sub-Linear Debugging
Source: Machined Learnings

No more MSR Silicon Valley

No more MSR Silicon Valley This news report is correct, the Microsoft Research Silicon Valley center has been cut. The New York lab has not been directly affected although obviously cross-lab collaborations are impacted, and we sympathize deeply with those involved. Most of the rest of MSR is not directly affected. I’m not privy to the rationale behind the decision,…
Original post: No more MSR Silicon Valley
Source: Machine Learning (Theory)

Reactive LDA Library

In this post, we introduce a parallel LDA (Latent Dirichlet Allocation) library. It’s available on Github. The library is written in Scala with Akka actors (hence the name Reactive). The underlying algorithm is based on vanilla Gibbs sampling. We will show that this approach scales much better than training LDA with collapsed Gibbs sampler, due to the easiness of parallelism.…
Original post: Reactive LDA Library
Source: Kifi