Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests" (⭐ 13)
Translation Quality Estimation (QE) is the task of predicting the quality of machine translation (MT) output without any reference. This task has gained increasing attention as an important component in the practical applications of MT. In this paper...
Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models. (⭐ 74)
Archived January 2, 2021, at the Wayback Machine - Maury Brown, Forbes SportsMoney, September 28, 2016 Strauss, Ben (April 23, 2022). "Some MLB broadcasters
SERVICING meaning: work done to repair a machine or vehicle or to keep it in good condition
Definition of 'servicing' servicing in British English (ˈsɜːvɪsɪŋ ) noun the act or process of overhauling or repairing (a car, machine, etc)
servicing (ˈsɜːvɪsɪŋ) n the act or process of overhauling or repairing (a car, machine, etc)
Non-smooth communication-efficient federated optimization is crucial for many machine learning applications, yet remains largely unexplored theoretically. Recent advancements have primarily focused on smooth convex and non-convex regimes, leaving a s...
Jan 22, 2026 · It is against Outlook.com policy to send mail from a machine which is an open proxy server, and it will be blocked from accessing some or all of Outlook.com servers as long as it remains …
Although gradient descent with Polyak's momentum is widely used in modern machine and deep learning, a concrete understanding of its effects on the training trajectory remains elusive. In this work, we empirically show that for linear diagonal networ...
Now the 2 routers are actually Windows 2008 R2 machines. Router 1 is actually a DC, router 2 is a standalone machine in case that makes any difference.
The evaluation of machine-generated image captions poses an interesting yet persistent challenge. Effective evaluation measures must consider numerous dimensions of similarity, including semantic relevance, visual structure, object interactions, capt...
The Automated Audio Captioning (AAC) task asks models to generate natural language descriptions of an audio input. Evaluating these machine-generated audio captions is a complex task that requires considering diverse factors, among them, auditory sce...
Passive tracking methods, such as phone and wearable sensing, have become dominant in monitoring human behaviors in modern ubiquitous computing studies. While there have been significant advances in machine-learning approaches to translate periods of...
Using different methods for laying out a graph can lead to very different visual appearances, with which the viewer perceives different information. Selecting a "good" layout method is thus important for visualizing a graph. The selection can be high...
Leveraging hypergraph structures to model advanced processes has gained much attention over the last few years in many areas, ranging from protein-interaction in computational biology to image retrieval using machine learning. Hypergraph models can p...
Counterfactuals -- expressing what might have been true under different circumstances -- have been widely applied in statistics and machine learning to help understand causal relationships. More recently, counterfactuals have begun to emerge as a tec...
A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci (⭐ 587)
1. Located or situated on a lower level or beneath something else: the under parts of a machine. 2. Lower in rank, power, or authority; subordinate. 3. Less than is required or customary: an under dose …
Federated Learning has been introduced as a new machine learning paradigm enhancing the use of local devices. At a server level, FL regularly aggregates models learned locally on distributed clients to obtain a more general model. Current solutions r...