3 accepted papers
In many real-world scenarios, agents operate across heterogeneous environments where the underlying dynamics and data-generating processes vary. Standard reinforcement learning and imitation learning methods often fail in such settings as they typically assume stationarity and learn policies that ov
The problem of using covariates to predict shapes of objects in a regression setting is important in many fields. A formal statistical approach, termed geodesic regression model, is commonly used for modeling and analyzing relationships between Euclidean predictors and shape responses. Despite its p…
Fast and effective image compression for multi-dimensional images has become increasingly important for efficient storage and transfer of massive amounts of high resolution images and videos. Desirable properties in compression methods include (1) high reconstruction quality at a wide range of compr…