research
∙
02/17/2023
Modelling and Kron reduction of power flow networks in directed graphs
Electrical grids are large-sized complex systems that require strong com...
share
research
∙
12/22/2022
Robust Meta-Representation Learning via Global Label Inference and Classification
Few-shot learning (FSL) is a central problem in meta-learning, where lea...
research
∙
08/09/2021
The Role of Global Labels in Few-Shot Classification and How to Infer Them
Few-shot learning (FSL) is a central problem in meta-learning, where lea...
research
∙
02/20/2020
Support-weighted Adversarial Imitation Learning
Adversarial Imitation Learning (AIL) is a broad family of imitation lear...
research
∙
02/20/2020
A Structured Prediction Approach for Conditional Meta-Learning
Optimization-based meta-learning algorithms are a powerful class of meth...
research
∙
05/16/2019
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
We consider the problem of imitation learning from a finite set of exper...
research
∙
10/07/2018
Real-Time Workload Classification during Driving using HyperNetworks
Classifying human cognitive states from behavioral and physiological sig...
research
∙
04/12/2017