research
∙
02/09/2023
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting
Sim2Real domain adaptation (DA) research focuses on the constrained sett...
share
research
∙
10/03/2022
Optimizing Data Collection for Machine Learning
Modern deep learning systems require huge data sets to achieve impressiv...
research
∙
07/04/2022
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks
Given a small training data set and a learning algorithm, how much more ...
research
∙
02/10/2022
Domain Adversarial Training: A Game Perspective
The dominant line of work in domain adaptation has focused on learning i...
research
∙
11/10/2021
Feature Generation for Long-tail Classification
The visual world naturally exhibits an imbalance in the number of object...
research
∙
06/21/2021
f-Domain-Adversarial Learning: Theory and Algorithms
Unsupervised domain adaptation is used in many machine learning applicat...
research
∙
06/05/2021
Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach
Given restrictions on the availability of data, active learning is the p...
research
∙
11/30/2020
Sim2SG: Sim-to-Real Scene Graph Generation for Transfer Learning
Scene graph (SG) generation has been gaining a lot of traction recently....
research
∙
07/01/2020
Ultrahyperbolic Representation Learning
In machine learning, data is usually represented in a (flat) Euclidean s...
research
∙
08/09/2019
