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Home > This Week in Machine Learning & Artificial Intelligence (AI) Podcast > Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk #160
Podcast: This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Episode:

Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk #160
Category: Technology
Duration: 00:40:08
Publish Date: 2018-07-02 12:36:26
Description:

In this episode, I'm joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University.

In this interview, Adji and I discuss two of her recent papers, the first, an accepted paper from this year’s ICML conference titled “Noisin: Unbiased Regularization for Recurrent Neural Networks,” which, as the name implies, presents a new way to regularize RNNs using noise injection. The second paper, an ICLR submission from last year titled “TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency,” debuts an RNN-based language model designed to capture the global semantic meaning relating words in a document via latent topics. We dive into the details behind both of these papers and I learn a ton along the way.

For complete show notes, visit twimlai.com/talk/160. 
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