Contrastive Learning

Contrastive learning is a self-supervised machine learning technique that aims to learn robust data representations by contrasting similar and dissimilar data points. Current research focuses on applying contrastive learning to diverse modalities, including images, audio, text, and time-series data, often within multimodal frameworks and using architectures like MoCo and SimCLR, and exploring its application in various tasks such as object detection, speaker verification, and image dehazing. This approach is significant because it allows for effective learning from unlabeled or weakly labeled data, improving model generalization and performance across numerous applications, particularly in scenarios with limited annotated data or significant domain shifts.

Papers

July 6, 2023

Contrast Is All You Need
Burak Kilic, Florix Bex, Albert Gatt
Contrastive Learning Text Classification Contrastive Method Data Scarce
Contrastive Label Disambiguation for Self-Supervised Terrain Traversability Learning in Off-Road Environments
Hanzhang Xue, Xiaochang Hu, Rui Xie, Hao Fu, Liang Xiao, Yiming Nie, Bin Dai
Contrastive Learning Environment Feature Road Environment Label Disambiguation Self Supervised Terrain
Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning
Hritam Basak, Zhaozheng Yin
Contrastive Learning Medical Image Segmentation Semi Supervised Unsupervised Domain Adaptation Domain Shift Consistency Regularization Semi Supervised Medical Image Segmentation Semi Supervised Domain Adaptation
Multi-Similarity Contrastive Learning
Emily Mu, John Guttag, Maggie Makar
Contrastive Learning Contrastive Loss Learning Generalizable

July 5, 2023

Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Data
Hongmin Cai, Xiaoke Huang, Zhengliang Liu, Wenxiong Liao, Haixing Dai, Zihao Wu, Dajiang Zhu, Hui Ren, Quanzheng Li, Tianming Liu, Xiang Li
Contrastive Learning Pre Trained Language Model Speech Analysis Alzheimer'S Disease Disease Detection Multimodal Approach Audio Data Clinical Narrative
Graph Contrastive Topic Model
Zheheng Luo, Lei Liu, Qianqian Xie, Sophia Ananiadou
Contrastive Learning Topic Embeddings Co Occurrence Graph
Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation
Jung Hyun Ryu, Jaeheyoung Jeon, Jewoong Cho, Myungjoo Kang 1
Contrastive Learning Recommendation System Sequential Recommendation Sequential Learning Fisher Weighted
STS-CCL: Spatial-Temporal Synchronous Contextual Contrastive Learning for Urban Traffic Forecasting
Lincan Li, Kaixiang Yang, Fengji Luo, Jichao Bi
Contrastive Learning Spatiotemporal Representation Spatiotemporal Graph

July 4, 2023

Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases
Yingji Li, Mengnan Du, Xin Wang, Ying Wang
Contrastive Learning Pre Trained Language Model Prompt Tuning Social Bias Debiasing Method Data Debiasing Two Stage Approach Adversarial Debiasing
SCAT: Robust Self-supervised Contrastive Learning via Adversarial Training for Text Classification
Junjie Wu, Dit-Yan Yeung
Contrastive Learning Adversarial Example Adversarial Training Text Classification Robust Version Textual Adversarial Attack

July 3, 2023

Learning Multi-Agent Communication with Contrastive Learning
Yat Long Lo, Biswa Sengupta, Jakob Foerster, Michael Noukhovitch
LeArning Abstract Contrastive Learning Mutual Information Multi Agent Communication Human Communication Multi Agent RL Effective Communication
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning
Yucheng Shi, Kaixiong Zhou, Ninghao Liu
Contrastive Learning Data Augmentation Graph Representation Learning Contrastive Objective Contrastive Augmentation

June 28, 2023

Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods
Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong
Contrastive Learning Self Supervised Representation Learning Visual Representation Learning Instance Discrimination Self Supervised Instance
Subclass-balancing Contrastive Learning for Long-tailed Recognition
Chengkai Hou, Jieyu Zhang, Haonan Wang, Tianyi Zhou
Contrastive Learning Long Tailed Recognition Tail Class
Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners
Bowen Shi, Xiaopeng Zhang, Yaoming Wang, Jin Li, Wenrui Dai, Junni Zou, Hongkai Xiong, Qi Tian
Contrastive Learning Representation Learning Masked Autoencoders Masked Image Modeling Token Masking
GraSS: Contrastive Learning with Gradient Guided Sampling Strategy for Remote Sensing Image Semantic Segmentation
Zhaoyang Zhang, Zhen Ren, Chao Tao, Yunsheng Zhang, Chengli Peng, Haifeng Li
Contrastive Learning Semantic Segmentation Contrastive Loss Gradient Based Contrastive Training Remote Sensing Image Semantic Segmentation Grass Growth

June 27, 2023

Generalized Out-of-distribution Fault Diagnosis (GOOFD) via Internal Contrastive Learning
Xingyue Wang, Hanrong Zhang, Xinlong Qiao, Ke Ma, Shuting Tao, Peng Peng, Hongwei Wang
Contrastive Learning New Framework Distribution Detection Fault Detection
FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation
Yunsung Chung, Chanho Lim, Chao Huang, Nassir Marrouche, Jihun Hamm
Contrastive Learning Background Generation Semi Supervised Segmentation

June 26, 2023

Hard Sample Mining Enabled Supervised Contrastive Feature Learning for Wind Turbine Pitch System Fault Diagnosis
Zixuan Wang, Bo Qin, Mengxuan Li, Chenlu Zhan, Mark D. Butala, Peng Peng, Hongwei Wang
Contrastive Learning Wind Turbine Hard Sample Mining
Histopathology Image Classification using Deep Manifold Contrastive Learning
Jing Wei Tan, Won-Ki Jeong
Contrastive Learning Image Classification Manifold Learning Supervised Contrastive Loss Geodesic Distance

Contrastive Learning

Papers

Contrast Is All You Need

Contrastive Label Disambiguation for Self-Supervised Terrain Traversability Learning in Off-Road Environments

Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning

Multi-Similarity Contrastive Learning

Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Data

Graph Contrastive Topic Model

Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation

STS-CCL: Spatial-Temporal Synchronous Contextual Contrastive Learning for Urban Traffic Forecasting

Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases

SCAT: Robust Self-supervised Contrastive Learning via Adversarial Training for Text Classification

Learning Multi-Agent Communication with Contrastive Learning

ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning

Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods

Subclass-balancing Contrastive Learning for Long-tailed Recognition

Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners

GraSS: Contrastive Learning with Gradient Guided Sampling Strategy for Remote Sensing Image Semantic Segmentation

Generalized Out-of-distribution Fault Diagnosis (GOOFD) via Internal Contrastive Learning

FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation

Hard Sample Mining Enabled Supervised Contrastive Feature Learning for Wind Turbine Pitch System Fault Diagnosis

Histopathology Image Classification using Deep Manifold Contrastive Learning