In real-world scenarios, labeled samples for dialogue summarization are
...
We consider dynamic pricing strategies in a streamed longitudinal data s...
Federated learning is a technique that enables a centralized server to l...
The recent advances of conversational recommendations provide a promisin...
Bundle recommender systems recommend sets of items (e.g., pants, shirt, ...
Action prediction aims to infer the forthcoming human action with
partia...
Learning the dynamics of spatiotemporal events is a fundamental problem....
Outlier detection is one of the most popular and continuously rising top...
Domain adaptation enhances generalizability of a model across domains wi...
Cross-Domain Detection (XDD) aims to train an object detector using labe...
Knowledge graphs suffer from sparsity which degrades the quality of
repr...
Visualization recommendation systems simplify exploratory data analysis ...
We study a general class of contextual bandits, where each context-actio...
Recently, neural-symbolic architectures have achieved success on commons...
Symbolic knowledge (e.g., entities, relations, and facts in a knowledge
...
We propose a novel algorithm, named Open-Edit, which is the first attemp...
Linear quadratic regulator (LQR) is one of the most popular frameworks t...
This paper studies the large-scale subspace clustering (LSSC) problem wi...
Decomposing images of document pages into high-level semantic regions (e...
Scene graph generation has received growing attention with the advanceme...
Deep neural networks have achieved great success on the image captioning...