🔬 Research Summary by Judy Hanwen Shen, a Computer Science Ph.D. student at Stanford University broadly working on algorithmic fairness, differential privacy, and explainability through the lens of data … [Read more...] about Unlocking Accuracy and Fairness in Differentially Private Image Classification
Technical Methods
Should you make your decisions on a WhIM? Data-driven decision-making using a What-If Machine for Evaluation of Hypothetical Scenarios
🔬 Research Summary by Jessica Echterhoff, a Ph.D. candidate in computer science at the University of California in San Diego. Her research focuses on human-data-centric artificial intelligence. [Original paper by … [Read more...] about Should you make your decisions on a WhIM? Data-driven decision-making using a What-If Machine for Evaluation of Hypothetical Scenarios
The Grand Illusion: The Myth of Software Portability and Implications for ML Progress
🔬 Research Summary by Fraser Mince, an independent machine learning researcher and a Senior Software Engineer at Waymark. [Original paper by Fraser Mince, Dzung Dinh, Jonas Kgomo, Neil Thompson, and Sara … [Read more...] about The Grand Illusion: The Myth of Software Portability and Implications for ML Progress
A Machine Learning Challenge or a Computer Security Problem?
🔬 Research Summary by Ilia Shumailov, a Ph.D. in Computer Science from the University of Cambridge, specializing in Machine Learning and Computer Security. During the PhD under the supervision of Prof Ross Anderson, Ilia … [Read more...] about A Machine Learning Challenge or a Computer Security Problem?
Assessing the nature of large language models: A caution against anthropocentrism
🔬 Research Summary by Ann Speed, a PhD in Cognitive Psychology and has worked across numerous disciplines in her 22-year career at Sandia National Laboratories. [Original paper by Ann Speed] Overview: … [Read more...] about Assessing the nature of large language models: A caution against anthropocentrism