Domain Adaptation
We introduce a framework for optimizing domain-specific dataset construction in foundation model training. Specifically, we seek a …
We introduce AgentAda, the first LLM-powered analytics agent that can learn and use new analytics skills to extract more specialized …
A popular approach for sequential decision-making is to perform simulator-based search
guided with Machine Learning (ML) methods like …
A popular approach for sequential decision-making is to perform simulator-based search
guided with Machine Learning (ML) methods like …
Domain randomization is a popular technique for improving domain transfer, often used in a zero-shot setting when the target domain is …
Single-view 3D shape reconstruction is an important but challenging problem, mainly for two reasons. First, as shape annotation is very …
The objective of unsupervised domain adaptation is to leverage features from a labeled source domain and learn a classifier for an …