International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?
Tech Xplore

Algorithm offers faster, more reliable control over language model outputs

A paper co-authored by Prof. Alex Lew has been selected as one of four "Outstanding Papers" at this year's Conference on Language Modeling (COLM 2025), held in Montreal in October.
IEEE

Malware Detection in PDF and PE Files Using Machine Learning and Feature Selection

Abstract: Malware detection is a crucial task in cybersecurity. Due to the dynamic nature of malware and the presence of new variants, signature-based malware detection solutions must be complemented ...
EurekAlert!

Towards better earthquake risk assessment with machine learning

“A building is only as strong as its foundation” is a common adage to signify the importance of having a stable and solid base to build upon. The type and design of foundation are important for ...
news.bloomberglaw

Navigating a Patent Gap for AI and Machine Learning Algorithms

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...
ascopubs.org

Machine-Learning Algorithms and Treatment Response in Advanced Melanoma

View all available purchase options and get full access to this article. The following represents disclosure information provided by authors of this manuscript. All relationships are considered ...
Phys.org

Quantum machine learning: Small-scale photonic quantum processor can already outperform classical counterparts

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...
Healio

Machine learning may assist in identifying pain trajectories after TKA

Please provide your email address to receive an email when new articles are posted on . A machine learning algorithm was able to identify pain archetypes after TKA. Predictors for difficult to control ...
Morningstar

MicroAlgo Inc. Develops Classifier Auto-Optimization Technology Based on Variational Quantum Algorithms, Accelerating the Advancement of Quantum Machine Learning

SHENZHEN, China, May 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO) announced today the launch of their latest classifier auto-optimization technology based on ...
ascopubs.org

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study The use of real-world data ...
Business Wire

Infleqtion Unveils Contextual Machine Learning (CML) at GTC 2025, Powering AI Breakthroughs with NVIDIA CUDA-Q and Quantum-Inspired Algorithms

CML Unlocks AI’s Full Potential with Enhanced Pattern Recognition, Prediction, and Real-Time Decision-Making for Defense, Autonomous Systems, and Next-Gen Computing BOULDER, Colo.--(BUSINESS ...
labs.sogeti

MACHINE LEARNING ALGORITHMS FOR TEST AUTOMATION

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...