6 citations · 9 across the 4 of their papers we have counts for
4 papers
Truly Self-Improving Agents Require Intrinsic Metacognitive Learning
Tennison Liu, Mihaela van der Schaar
Self-improving agents aim to continuously acquire new capabilities with minimal supervision. However, current approaches face two key limitations: their self-improvement processes…
Agents Require Metacognitive and Strategic Reasoning to Succeed in the Coming Labor Markets
Simpson Zhang, Tennison Liu, Mihaela van der Schaar
Current labor markets are strongly affected by the economic forces of adverse selection, moral hazard, and reputation, each of which arises due to …
Automatically Learning Hybrid Digital Twins of Dynamical Systems
Samuel Holt, Tennison Liu, Mihaela van der Schaar
Digital Twins (DTs) are computational models that simulate the states and temporal dynamics of real-world systems, playing a crucial role in prediction, understanding, and decision…
Unveiling the Power of Sparse Neural Networks for Feature Selection
Zahra Atashgahi, Tennison Liu, Mykola Pechenizkiy +3
Sparse Neural Networks (SNNs) have emerged as powerful tools for efficient feature selection. Leveraging the dynamic sparse training (DST) algorithms within SNNs has demonstrated p…