This paper introduces a new framework for open-domain question answering in which the
retriever and the reader iteratively interact with each other. The framework is agnostic to the …

Implicit probabilistic models are models defined naturally in terms of a sampling procedure
and often induces a likelihood function that cannot be expressed explicitly. We develop a …

Abstract Generative Adversarial Networks (GANs) have brought about rapid progress
towards generating photorealistic images. Yet the equitable allocation of their modeling …

Approximate nearest neighbor search on high-dimensional vectors is a crucial component
for numerous applications in various fields. To solve this problem efficiently, dozens of …

Many tasks in computer vision and graphics fall within the framework of conditional image
synthesis. In recent years, generative adversarial nets have delivered impressive advances …

For problems with large output spaces, evaluation of the loss function and its gradient are
expensive, typically taking linear time in the size of the output space. Recently, methods …

Nearest neighbor search using random projection trees has recently been shown to achieve
superior performance, in terms of better accuracy while retrieving less number of data points …

Scalable real-time assortment optimization has become essential in e-commerce operations
due to the need for personalization and the availability of a large variety of items. While this …

Prior work inspired by compression algorithms has described how the Burrows Wheeler
Transform can be used to create a distance measure for bioinformatics problems. We …

One limitation of existing Transformer-based models is that they cannot handle very long
sequences as input since their self-attention operations exhibit quadratic time and space …