Using lobbying data from OpenSecrets.org, we offer several experiments applying machine learning techniques to predict if a piece of legislation (US bill) has been subjected to lobbying activities or not. We also investigate the influence of the inte...
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computer numerical control (CNC) router is a computer-controlled cutting machine which typically mounts a hand-held router as a spindle which is used for
[1] Archived 2012-05-14 at the Wayback Machine, NAMS Official Website. General NAMS Official Website NAMS Certified Menopause Practitioner Directory
We study utilizing auxiliary information in training data to improve the trustworthiness of machine learning models. Specifically, in the context of image classification, we propose to optimize a training objective that incorporates bounding box info...
"Understanding the impact of technology in audit and finance". Dubai Financial Services Authority. 13 December 2017. "Machine Learning in Auditing". The CPA Journal
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Machine learning for Anonymous detection of an alcoholic by EEG signals (⭐ 31)
Preparing for machine learning interviews (⭐ 903)
Network intrusion attacks are a known threat. To detect such attacks, network intrusion detection systems (NIDSs) have been developed and deployed. These systems apply machine learning models to high-dimensional vectors of features extracted from net...
The OpenAPI Specification, previously known as the Swagger Specification, is a specification for a machine-readable interface definition language for
Testing RESTful API is increasingly important in quality assurance of cloud-native applications. Recent advances in machine learning (ML) techniques have demonstrated that various testing activities can be performed automatically by large language mo...
While large machine learning models have shown remarkable performance in various domains, their training typically requires iterating for many passes over the training data. However, due to computational and memory constraints and potential privacy c...
This paper considers single-machine scheduling problems in which a given solution, i.e. an ordered set of jobs, has to be improved as much as possible by re-sequencing the jobs. The need for rescheduling may arise in different contexts, e.g. due to c...
In this paper, we explore the utility of translationese as synthetic data created using machine translation for pre-training language models (LMs) for low-resource languages (LRLs). Our simple methodology consists of translating large amounts of web-...
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models. (⭐ 592)