research
∙
10/09/2022
Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport
Few-shot classification aims to learn a classifier to recognize unseen c...
share
research
∙
08/05/2022
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification
Imbalanced data pose challenges for deep learning based classification m...
research
∙
03/03/2022
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings
A topic model is often formulated as a generative model that explains ho...
research
∙
10/18/2021
Learning Prototype-oriented Set Representations for Meta-Learning
Learning from set-structured data is a fundamental problem that has rece...
research
∙
05/10/2021
Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning
Observing a set of images and their corresponding paragraph-captions, a ...
research
∙
09/28/2020
Variational Temporal Deep Generative Model for Radar HRRP Target Recognition
We develop a recurrent gamma belief network (rGBN) for radar automatic t...
research
∙
12/21/2019
Recurrent Hierarchical Topic-Guided Neural Language Models
To simultaneously capture syntax and global semantics from a text corpus...
research
∙
10/26/2018
Deep Poisson gamma dynamical systems
We develop deep Poisson-gamma dynamical systems (DPGDS) to model sequent...
research
∙
03/04/2018
