Search Results for author:
Found 4 papers, 2 papers with code
MAViC: Multimodal Active Learning for Video Captioning
Our approach integrates semantic similarity and uncertainty of both visual and language dimensions in the acquisition function.
Diversity vs. Recognizability: Human-like generalization in one-shot generative models
Robust generalization to new concepts has long remained a distinctive feature of human intelligence.
Adaptive Methods for Aggregated Domain Generalization
In this paper, we propose a domain-adaptive approach to this problem, which operates in two steps: (a) we cluster training data within a carefully chosen feature space to create pseudo-domains, and (b) using these pseudo-domains we learn a domain-adaptive classifier that makes predictions using information about both the input and the pseudo-domain it belongs to.
Ranked #16 on
Domain Generalization
on PACS
Content-Based Personalized Recommender System Using Entity Embeddings
Recommender systems are a class of machine learning algorithms that provide relevant recommendations to a user based on the user's interaction with similar items or based on the content of the item.
