Science & Technology

Generative Adversarial Networks (GANs) are a popular generative modelling approach known for producing appealing samples, but their theoretical properties are not yet fully understood, and they are notably difficult to train. In the first part of this talk, I will provide some insights on why GANs are a more meaningful …

Automatic text summarization is an important tool for enhancing users’ ability to make decisions in the face of overwhelming amounts of data. Key to making this technology useful and practical is to have high-performing systems that work on a variety of texts and settings. However, existing systems are usually developed …

We shape our tools and thereafter our tools shape us.

The Iowa Caucuses kicked off the Democratic primary on February 3, 2020 — but because of a bad app, it took days to report results. It’s a bad sign for 2020, and a look at just how fragile our election infrastructure has gotten — but the problem is even bigger …

Standard neural sequence generation methods assume a pre-specified generation order, such as left-to-right generation. Despite its wild success in recent years, there’s a lingering question of whether this is necessary and if there is any other way to generate such a sequence in an order automatically learned from data without …

The only thing I know is that I know nothing.

Learning of layered or “deep” representations has recently enabled low-cost sensors for autonomous vehicles and efficient automated analysis of visual semantics in online media. But these models have typically required prohibitive amounts of training data, and thus may only work well in the environment they have been trained in. I’ll …

Humans are much better than current AI systems at generalizing out-of-distribution. What ingredients can bring us closer to that level of competence? We propose 4 ingredients combined: (a) meta-learning (to learn end-to-end to generalize to modified distributions, sampled from a distribution over distributions), (b) designing modular architectures with the property …

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