research
∙
05/24/2023
Training Energy-Based Normalizing Flow with Score-Matching Objectives
In this paper, we establish a connection between the parameterization of...
share
research
∙
04/12/2023
Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA
Recent works demonstrate a remarkable ability to customize text-to-image...
research
∙
06/30/2022
Language model compression with weighted low-rank factorization
Factorizing a large matrix into small matrices is a popular strategy for...
research
∙
03/31/2022
A Closer Look at Rehearsal-Free Continual Learning
Continual learning describes a setting where machine learning models lea...
research
∙
01/05/2022
Hyperparameter-free Continuous Learning for Domain Classification in Natural Language Understanding
Domain classification is the fundamental task in natural language unders...
research
∙
10/27/2021
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition
It is well known that vision classification models suffer from poor cali...
research
∙
06/28/2021
Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU
Intent classification is a major task in spoken language understanding (...
research
∙
10/22/2020
Posterior Re-calibration for Imbalanced Datasets
Neural Networks can perform poorly when the training label distribution ...
research
∙
02/26/2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data
Deep neural networks have attained remarkable performance when applied t...
research
∙
01/02/2019
Multi-class Classification without Multi-class Labels
This work presents a new strategy for multi-class classification that re...
research
∙
10/30/2018
Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines
Continual learning has received a great deal of attention recently with ...
research
∙
06/28/2018
A probabilistic constrained clustering for transfer learning and image category discovery
Neural network-based clustering has recently gained popularity, and in p...
research
∙
03/17/2018
Learning to Cluster for Proposal-Free Instance Segmentation
This work proposed a novel learning objective to train a deep neural net...
research
∙
11/28/2017
Learning to cluster in order to Transfer across domains and tasks
This paper introduces a novel method to perform transfer learning across...
research
∙
09/02/2017
Learning Loss for Knowledge Distillation with Conditional Adversarial Networks
There is an increasing interest on accelerating neural networks for real...
research
∙
12/05/2016
Deep Image Category Discovery using a Transferred Similarity Function
Automatically discovering image categories in unlabeled natural images i...
research
∙
11/19/2015