NRDLC, a unified framework that removes noisy labels and selects informative features simultaneously for partial multi-label ...

Amin’s research applies AI and machine learning—especially multimodal, text, unsupervised, and graph-based methods—to turn ...

In the field of artificial intelligence, machine learning is a branch that uses data and algorithms to imitate human learning. It's an ongoing process in which computers can improve their accuracy ...

The Limits of Ad Creative Optimization and the Breakthroughs Brought by LLM and Reinforcement LearningIn digital marketing, ad creatives are one of the most critical variables influencing conversions ...

Machine learning models are often drowning in data, but the problem is not always the sheer volume of samples. Increasingly, ...

Unlocking healthcare data requires more than algorithms—it demands validation, context, and clinical collaboration.

OpenAI said in a security post published September 30, 2026 that it identified and disrupted a coordinated campaign designed ...

Construction risk decisions often begin with fragmented financial, compliance, and operational information. At ConstructionBevy, machine-learning scientist Chandana Dayapule worked on ...

From SQL aggregation to 'secure collaborative machine learning'The tectonic shift in ad tech, triggered by the phased elimination of third-party cookies, has fundamentally overturned the premises of ...

A review published in ENGINEERING Energy systematically evaluates how artificial intelligence is transforming waste plastic pyrolysis. By ...

Ghost in the Machine reveals AI’s troubled history and present-day impacts. Ghost in the Machine reveals how the human values, biases, and power structures behind artificial intelligence are shaping ...

Abstract: Soil salinization in coastal regions poses a serious threat to sustainable agricultural development. Feature selection is critical for improving soil salinity inversion accuracy. To this end ...