Search Results for author:
Found 4 papers, 0 papers with code
Real World Time Series Benchmark Datasets with Distribution Shifts: Global Crude Oil Price and Volatility
The scarcity of task-labeled time-series benchmarks in the financial domain hinders progress in continual learning.
Mixture of basis for interpretable continual learning with distribution shifts
In this paper we consider settings in which the data distribution(task) shifts abruptly and the timing of these shifts are not known.
Lagrangian Duality in Reinforcement Learning
Although duality is used extensively in certain fields, such as supervised learning in machine learning, it has been much less explored in others, such as reinforcement learning (RL).
Complex Skill Acquisition Through Simple Skill Imitation Learning
Humans often think of complex tasks as combinations of simpler subtasks in order to learn those complex tasks more efficiently.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
