1

McGan: Mean and Covariance Feature Matching GAN

We introduce new families of Integral Probability Metrics (IPM) for training Generative Adversarial Networks (GAN). Our IPMs are based on matching statistics of distributions embedded in a finite d...

Co-Occurring Directions Sketching for Approximate Matrix Multiply

We introduce co-occurring directions sketching, a deterministic algorithm for approximate matrix product (AMM), in the streaming model. We show that co-occurring directions achieves a better error ...

Local Group Invariant Representations via Orbit Embeddings

Invariance to nuisance transformations is one of the desirable properties of effective representations. We consider transformations that form a group and propose an approach based on kernel methods...

Self-Critical Sequence Training for Image Captioning

On efficiency and low sample complexity in phase retrieval

In this paper we show that the problem of phase retrieval can be efficiently and provably solved via an alternating minimization algorithm suitably initialized. Our initialization is based on One Bit Phase Retrieval that we introduced in [1], where …