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06/13/2023
Semi-supervised learning made simple with self-supervised clustering
Self-supervised learning models have been shown to learn rich visual rep...
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12/09/2022
A soft nearest-neighbor framework for continual semi-supervised learning
Despite significant advances, the performance of state-of-the-art contin...
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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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03/26/2022
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
A fundamental and challenging problem in deep learning is catastrophic f...
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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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08/19/2021
A Unified Objective for Novel Class Discovery
In this paper, we study the problem of Novel Class Discovery (NCD). NCD ...
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08/03/2021
Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning
This paper presents solo-learn, a library of self-supervised methods for...
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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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08/04/2020
Online Continual Learning under Extreme Memory Constraints
Continual Learning (CL) aims to develop agents emulating the human abili...
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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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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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08/31/2017
Abnormal Event Detection in Videos using Generative Adversarial Nets
In this paper we address the abnormality detection problem in crowded sc...
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06/23/2017
Training Adversarial Discriminators for Cross-channel Abnormal Event Detection in Crowds
Abnormal crowd behaviour detection attracts a large interest due to its ...
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05/03/2017
FOIL it! Find One mismatch between Image and Language caption
In this paper, we aim to understand whether current language and vision ...
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11/21/2016
Efficient Convolutional Neural Network with Binary Quantization Layer
In this paper we introduce a novel method for segmentation that can bene...
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10/02/2016
Plug-and-Play CNN for Crowd Motion Analysis: An Application in Abnormal Event Detection
Most of the crowd abnormal event detection methods rely on complex hand-...
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09/29/2016
CNN-aware Binary Map for General Semantic Segmentation
In this paper we introduce a novel method for general semantic segmentat...
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07/26/2016
Emotion-Based Crowd Representation for Abnormality Detection
In crowd behavior understanding, a model of crowd behavior need to be tr...
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05/24/2016
Self Paced Deep Learning for Weakly Supervised Object Detection
In a weakly-supervised scenario object detectors need to be trained usin...
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12/23/2015
