A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...
Modeling counterparty risk is computationally challenging because it requires the simultaneous evaluation of all trades between each counterparty under both market and credit risk. We present a ...
Interesting Engineering on MSN
New adaptive system lets robots replicate human touch with far less training data
Researchers in Japan have developed an adaptive motion reproduction system that allows robots to ...
Pantelis Samartsidis, Claudia R. Eickhoff, Simon B. Eickhoff, Tor D. Wager, Lisa Feldman Barrett, Shir Atzil, Timothy D. Johnson, Thomas E. Nichols Journal of the ...
This research from Keio University leverages Gaussian process regression, enabling robots to intuitively adjust grip based on ...
We propose a nested Gaussian process (nGP) as a locally adaptive prior for Bayesian nonparametric regression. Specified through a set of stochastic differential equations (SDEs), the nGP imposes a ...
When applying machine learning to trading strategy, two inevitable practical issues are achieving interpretable results and securing robustness to market changes. To overcome these challenges, ...
Tech Xplore on MSN
Adaptive motion system helps robots achieve human-like dexterity with minimal data
Despite rapid robotic automation advancements, most systems struggle to adapt their pre-trained movements to dynamic ...
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