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...
Highly parallelized workloads like machine learning training, inferences and general HPC tasks are greatly accelerated using GPU devices. In a cloud computing cluster, serving a GPU's computation power through multi-tasks sharing is highly demanded s...
Quantum noise fundamentally limits the utility of near-term quantum devices, making error mitigation essential for practical quantum computation. While traditional quantum error correction codes require substantial qubit overhead and complex syndrome...
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics
The vulnerabilities to backdoor attacks have recently threatened the trustworthiness of machine learning models in practical applications. Conventional wisdom suggests that not everyone can be an attacker since the process of designing the trigger ge...
Superwash Merino Yarns are 100% Superwash Wool. A natural fibre that's perfect for machine washing and drying. Shop online with Wool & Waves today. The wool used in Merino Superwash has been …
Mar 24, 2025 · “Superwash” is a process that chemically treats yarn (typically wool) so it won’t felt in the machine. This treatment slicks down the wool fibres, so they can’t grab onto each other and tangle, …
'Superwash' is a fibre that has been treated or processed in a way that allows it to be machine washable, and therefore, will not felt. This makes Superwash yarns especially perfect for makers who …
It becomes a significant challenge to predict customer behavior and retain an existing customer with the rapid growth of digitization which opens up more opportunities for customers to choose from subscription-based products and services model. Since...
My research advances econometric methodology at the intersection of time series forecasting, machine learning, and foundation models, with applications spanning macroeconomic policy, climate science, …