Customer-obsessed science

Due to the limited connectivity of gate model quantum devices, logical quantum circuits must be compiled to target hardware before they can be executed. Often, this process involves the insertion of SWAP gates into the logical circuit, usually increasing the depth of the circuit, achieved by solving a so-called qubit assignment and routing problem. Recently, a number of integer linear programming (ILP)

For industrial learning-to-rank (LTR) systems, it is common that the output of a ranking model is modified, either as a results of post-processing logic that enforces business requirements, or as a result of unforeseen design flaws or bugs present in real-world production systems. This poses a challenge for deploying off-policy learning and evaluation methods, as these often rely on the assumption that

Online advertising is typically implemented via real-time bidding, and advertising campaigns are then defined as extremely high-dimensional optimization problems. Advertisers often define a campaign by an order consisting of multiple lines. Campaign delivery constraints may be imposed on the order as a whole and on each ad line. E.g., there may be budget and cost per click constraints on the order and on

In this paper, we study the problem of detecting objects with rich textual features from images. One such example is to detect stopwatch regions from sports videos. We propose a novel approach that combines image feature with text features for object detection, and benchmark against traditional OCR-based method and object detection method using image feature only. In particular, we modify the Faster R-CNN

Federated Learning (FL) offers a privacy-preserving approach to model training, allowing edge devices to learn collaboratively without sharing data. Edge devices like Alexa and Siri are prospective sources of unlabeled audio data that can be tapped to learn robust audio representations. In this work, we bring Self-supervised Learning (SSL) and FL together to learn representations for Automatic Speech Recognition