Give us a call or drop by anytime, we endeavor to answer all inquiries within 24 hours.
PO Box 16122 Collins Street West Victoria, Australia
info@domain.com / example@domain.com
Phone: + (066) 0760 0260 / + (057) 0760 0560
Zoom ID: https://cuboulder.zoom.us/j/2251625831 Password: i-aim Yannis Kevrekidis, Johns Hopkins University "Manifold Learning for Free Energy Surface Exploration" Abstract: TBA About the Speaker: TBA
Title Deep Learning for Market Design: Fairness, Robustness, and Expressiveness John Dickerson, Assistant Professor of Computer Science, University of Maryland; Chief Scientist, Arthur AI AbstractThe design of revenue-maximizing auctions with strong incentive guarantees is a core concern of economic theory. Computational auctions enable online advertising, sourcing, spectrum allocation, and myriad financial markets. Analytic progress in this […]
Thoughts and Efforts on AI Meeting Production Abstract: Machine Learning systems for complex tasks - such as controlling industrial manufacturing processes in real-time; or writing medical imaging case reports – are becoming increasingly sophisticated and consist of a large number of data, model, algorithm, and system elements and modules. Traditional benchmark/leaderboard-driven bespoke approaches in the […]
Zoom ID: https://cuboulder.zoom.us/j/2251625831 Password: i-aim Margaret Murnane, CU Boulder "Extracting the Structural, Mechanical, and Transport Properties of Nanostructured Materials" Abstract: TBA About the Speaker: TBA
Title: A modern take on Huber regression Abstract: In the first part of the talk, we discuss the use of a penalized Huber M-estimator for high-dimensional linear regression. We explain how a fairly straightforward analysis yields high-probability error bounds that hold even when the additive errors are heavy-tailed. However, the parameter governing the shape of […]
Zoom ID: https://cuboulder.zoom.us/j/2251625831 Password: i-aim Markus Buehler, MIT "Bioinspired AI for Hierarchical Material Design: Modeling, Design, and Manufacturing" Abstract: TBA About the Speaker: TBA
Title: Causal Effect Inference: A Machine Learning Approach Abstract A major challenge in the domain of healthcare is ascertaining whether a given treatment influences or determines an outcome—for instance, whether there is a survival benefit to prescribing a certain medication. Current treatment guidelines have been developed with the “average” patient in mind, but the reality […]
Or Cohen, Lyft Machine Learning for Spatio-Temporal Problems May 3, 2021, 5pm: Join Zoom Meeting https://ucsd.zoom.us/j/95036249217?pwd=a2kwSFg2ZXMvc21yMHZLRVR2c0pqUT09 Abstract: Machine learning is used widely at Lyft. A few examples include predicting where and when ride requests will happen, predicting travel time between two locations or predicting the probability for a passenger to cancel his/her ride. Such […]
Title: Unavoidable Tensions in Explaining Algorithmic Decisions Abstract: Recent developments in methods for explaining the decisions of machine learning models have been widely embraced for their ability to provide transparency and accountability without limiting model complexity or compelling model disclosure. Yet applying these methods is far from straightforward and they rarely prove a cure all. This talk […]