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11/09/2022
miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings
This paper presents miCSE, a mutual information-based Contrastive learni...
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04/11/2022
Mixture-of-experts VAEs can disregard variation in surjective multimodal data
Machine learning systems are often deployed in domains that entail data ...
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03/15/2022
SCD: Self-Contrastive Decorrelation for Sentence Embeddings
In this paper, we propose Self-Contrastive Decorrelation (SCD), a self-s...
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09/10/2021
Attention-based Contrastive Learning for Winograd Schemas
Self-supervised learning has recently attracted considerable attention i...
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09/10/2021
Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language Models
Can we get existing language models and refine them for zero-shot common...
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11/17/2020
Multimodal Prototypical Networks for Few-shot Learning
Although providing exceptional results for many computer vision tasks, s...
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10/22/2020
Learning Graph-Based Priors for Generalized Zero-Shot Learning
The task of zero-shot learning (ZSL) requires correctly predicting the l...
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05/02/2020
Contrastive Self-Supervised Learning for Commonsense Reasoning
We propose a self-supervised method to solve Pronoun Disambiguation and ...
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12/11/2019
Multimodal Self-Supervised Learning for Medical Image Analysis
In this paper, we propose a self-supervised learning approach that lever...
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11/30/2019
Pruning at a Glance: Global Neural Pruning for Model Compression
Deep Learning models have become the dominant approach in several areas ...
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11/06/2019
Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds
Automatic question generation aims at the generation of questions from a...
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05/31/2019
Attention Is (not) All You Need for Commonsense Reasoning
The recently introduced BERT model exhibits strong performance on severa...
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05/15/2019
Budget-Aware Adapters for Multi-Domain Learning
Multi-Domain Learning (MDL) refers to the problem of learning a set of m...
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04/05/2019
Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning
Models trained in the context of continual learning (CL) should be able ...
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01/04/2019
Low-Shot Learning from Imaginary 3D Model
Since the advent of deep learning, neural networks have demonstrated rem...
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11/22/2018
Self Paced Adversarial Training for Multimodal Few-shot Learning
State-of-the-art deep learning algorithms yield remarkable results in ma...
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09/12/2018
The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA
We introduce MASSES, a simple evaluation metric for the task of Visual Q...
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06/13/2018
Cross-modal Hallucination for Few-shot Fine-grained Recognition
State-of-the-art deep learning algorithms generally require large amount...
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04/04/2018
Gaussian Process Uncertainty in Age Estimation as a Measure of Brain Abnormality
Multivariate regression models for age estimation are a powerful tool fo...
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12/20/2017
Differentially Private Federated Learning: A Client Level Perspective
Federated learning is a recent advance in privacy protection. In this co...
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05/23/2017
A Multi-Armed Bandit to Smartly Select a Training Set from Big Medical Data
With the availability of big medical image data, the selection of an ade...
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02/27/2017
