The combination of machines and humans for translation is effective, with many studies showing productivity gains when humans post-edit machine-translated output instead of translating from scratch. To take full advantage of this combination, we need...
As machine learning becomes more widely adopted across domains, it is critical that researchers and ML engineers think about the inherent biases in the data that may be perpetuated by the model. Recently, many studies have shown that such biases are...
A Data Science project that applies machine learning and geospatial analysis to a dataset of 332 ancient Mayan sites. This project predicts the modern regional location of archaeological sites based on their geographic coordinates and visualizes their distribu…
Cephalometric Landmark Detection is the process of identifying key areas for cephalometry. Each landmark is a single GT point labelled by a clinician. A machine learning model predicts the probability locus of a landmark represented by a heatmap. Thi...
original on 2 April 2015. Retrieved 13 March 2015. 'Iranian Artists and Writers in Exile Archived 25 June 2009 at the Wayback Machine, Iranian Artists and
Abundance of movie data across the internet makes it an obvious candidate for machine learning and knowledge discovery. But most researches are directed towards bi-polar classification of movie or generation of a movie recommendation system based on...
People learning new concepts can often generalize successfully from just a single example, yet machine learning algorithms typically require tens or hundreds of examples to perform with similar accuracy. People can also use learned concepts in richer ways than…
Federated learning (FL) allows multiple data-owners to collaboratively train machine learning models by exchanging local gradients, while keeping their private data on-device. To simultaneously enhance privacy and training efficiency, recently parame...
A fundamental problem in quantum many-body physics is that of finding ground states of local Hamiltonians. A number of recent works gave provably efficient machine learning (ML) algorithms for learning ground states. Specifically, [Huang et al. Scien...
Spoken language translation (SLT) is becoming more important in the increasingly globalized world, both from a social and economic point of view. It is one of the major challenges for automatic speech recognition (ASR) and machine translation (MT), d...
This study discusses how insights retrieved from subscriber data can impact decision-making in telecommunications, focusing on predictive modeling using machine learning techniques such as the ARIMA model. The study explores time series forecasting t...
self-defense". "'Boogaloo Bois' face new charges for possessing machine guns, silencers". Star Tribune. November 7, 2020. Retrieved March 21, 2021. Sepic, Matt
2018. Archived 2019-05-05 at the Wayback Machine (in French) Wave.fr: Zola drops a new freestyle named “Manger”[permanent dead link] "Zola discography".
a virtual machine you need to extend. (⭐ 0)
The purpose of this paper is to explore the question "to what extent could we produce formal, machine-verifiable, proofs in real algebraic geometry?" The question has been asked before but as yet the leading algorithms for answering such questions ha...
Climate change in India is one of the most alarming problems faced by our community. Due to adverse and sudden changes in climate in past few years, mankind is at threat. Various impacts of climate change include extreme heat, changing rainfall patte...
Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of each feature's value to the prediction. This requires a scalar prediction as in binary classification,...
The first ever human vs. computer no-limit Texas hold 'em competition took place from April 24-May 8, 2015 at River's Casino in Pittsburgh, PA. In this article I present my thoughts on the competition design, agent architecture, and lessons learned....
Recent advancements in neural language modelling make it possible to rapidly generate vast amounts of human-sounding text. The capabilities of humans and automatic discriminators to detect machine-generated text have been a large source of research i...
This work presents an analysis of the Duckworth-Lewis-Stern (DLS) method for One Day International (ODI) cricket matches. The accuracy of the DLS method is compared against various supervised learning algorithms for result prediction. The result of a...