Moving in an uncertain world: robust and adaptive control of locomotion from organisms to machine intelligence
Whether walking, running, slithering, or flying, organisms display a remarkable ability to
move through complex and uncertain environments. In particular, animals have evolved to …
move through complex and uncertain environments. In particular, animals have evolved to …
Prospective Learning: Learning for a Dynamic Future
In real-world applications, the distribution of the data, and our goals, evolve over time. The
prevailing theoretical framework for studying machine learning, namely probably …
prevailing theoretical framework for studying machine learning, namely probably …
Accuracy and Fairness for Web-Based Content Analysis under Temporal Shifts and Delayed Labeling
Web-based content analysis tasks, such as labeling toxicity, misinformation, or spam often
rely on machine learning models to achieve cost and scale efficiencies. As these models …
rely on machine learning models to achieve cost and scale efficiencies. As these models …
Transformers for Supervised Online Continual Learning
Transformers have become the dominant architecture for sequence modeling tasks such as
natural language processing or audio processing, and they are now even considered for …
natural language processing or audio processing, and they are now even considered for …
Fair and Accurate Machine Learning in Dynamic and Multi-Domain Settings
AAS Almuzaini - 2024 - search.proquest.com
A multitude of decision-making tasks, such as content moderation, medical diagnosis,
misinformation detection, and recidivism prediction, are increasingly being automated due to …
misinformation detection, and recidivism prediction, are increasingly being automated due to …