IEEE

Unsupervised Learning-Based Low-Complexity Integrated Sensing and Communication Precoder Design

Abstract: This study proposes an unsupervised deep learning-based (DL-based) approach to precoding design for integrated sensing and communication (ISAC) systems. Designing a dynamic precoder that can ...

They aren’t colleges. But they promise fast, cheap college credits.

Unaccredited and unregulated online learning platforms offer unlimited transferrable college courses that can be completed in ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Frontiers

Are S.M.A.R.T goals really smart? The psychological effects of goal-setting in a learning task

Aim: Specific, Measurable, Achievable, Realistic, Time-bound (SMART) goals are commonly used in educational settings as a strategy to optimise learning. However, research and theory suggest that such ...
GitHub

Nested Learning Reproduction

Mechanism-level reproduction of Google's Nested Learning (HOPE) architecture (HOPE blocks, CMS, and Self‑Modifying TITANs), matching the quality bar set by lucidrains' TITAN reference while remaining ...
IEEE

Unsupervised Feature Selection for High-Order Embedding Learning and Sparse Learning

Abstract: The majority of the unsupervised feature selection methods usually explore the first-order similarity of the data while ignoring the high-order similarity of the instances, which makes it ...