Statistical Learning
Fairness A ware Counterfactuals for Subgroups
Machine learning is now an integral part of decision-making processes across various domains, e.g., medical applications [
Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network
Unfortunately, even for standard linear networks in regression setting, a comprehensive characterization of the implicit bias is still an open problem.
MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection
However, these methods still suffer from an over-generalization issue and fail to deliver consistently high performance.
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
With more than 4.5 million patent documents, HUPD is two to three times larger than comparable corpora.
Optimistic Meta-Gradients
We study the connection between gradient-based meta-learning and convex optimisation. We observe that gradient descent with momentum is a special case of meta-gradients, and building on recent results in optimisation, we prove convergence rates for meta-learning in the single task setting.