entity · derived
Machine learning
Derived node: assembled mechanically from the claims carrying machine-learning. A roster, not an adjudicated definition.
Every claim under this term
- 2939127-023 : Leveraging the big data collected through Legal Tech solutions and blockchain applications in combination with machine learning produces more creative and faster tools, which in turn generates a surge
- 2998033-021 : Repeated use of the same dataset by data scientists creates an overfitting risk: the training model fits the test set so closely that its performance on a different dataset degrades.
- 3409548-003 : Current hedge fund trading technology is hard coded by humans, whereas deep learning systems can be given a simple command and derive a result from data on their own; this is the operative difference
- 3409548-005 : Systematic, computer model driven funds do not reliably outperform human managed funds: research finds the typical systematic fund does not always perform as well as funds run by human managers.
- 3409548-007 : Machine learning improves portfolio diversification by searching for instruments that are uncorrelated with each other and that still match the requirements of the target risk profile.
- 3409548-009 : Repeated use of the same data set by data scientists creates an overfitting risk: the training model overfits the test set, which limits the performance of the applied model on a different dataset.
- 3409548-025 : Machine learning applied to execution algorithms lets large orders be split into thousands of smaller transactions without moving the market, with the algorithm adjusting its aggressiveness to market
- 3409548-026 : Artificial intelligence and machine learning are used far more heavily for idea generation and portfolio optimization than for execution: two thirds of surveyed funds use them to generate trading idea
- 5245185-028 : Anomaly detection and behavioral analysis models trained on agent data may replicate the biases in that data and fail to detect novel deviations absent from the training set.
- 5541658-001 : The limitations of rule-based legal expert systems drove the field toward case-based reasoning in the 1990s and machine learning in the early 2000s, because data-driven approaches allow legal AI to op