Federated learning is a recently proposed distributed machine learning paradigm for privacy
preservation, which has found a wide range of applications where data privacy is of primary …

Neural Architecture Search (NAS) methods have been growing in popularity. These
techniques have been fundamental to automate and speed up the time consuming and error …

Abstract We present Mobile Video Networks (MoViNets), a family of computation and
memory efficient video networks that can operate on streaming video for online inference …

Given the recent impressive accomplishments of language models (LMs) for code
generation, we explore the use of LMs as general adaptive mutation and crossover …

Large Transformer models have been central to recent advances in natural language
processing. The training and inference costs of these models, however, have grown rapidly …

In the past decade, advances in deep learning have resulted in breakthroughs in a variety of
areas, including computer vision, natural language understanding, speech recognition, and …

Neural architecture search (NAS) has attracted a lot of attention and has been illustrated to
bring tangible benefits in a large number of applications in the past few years. Architecture …

Abstract Neural Architecture Search methods are effective but often use complex algorithms
to come up with the best architecture. We propose an approach with three basic steps that is …

A myriad of recent breakthroughs in hand-crafted neural architectures for visual recognition
have highlighted the urgent need to explore hybrid architectures consisting of diversified …

Inverted bottleneck layers, which are built upon depthwise convolutions, have been the
predominant building blocks in state-of-the-art object detection models on mobile devices. In …