Generalizable Feature

Generalizable features in machine learning aim to create models that perform well on unseen data, overcoming the limitations of models trained only on specific datasets. Current research focuses on developing techniques to learn these features, employing methods like adversarial training, multi-task learning, and diffusion models, often within architectures such as neural radiance fields and Faster R-CNN. This pursuit is crucial for improving the robustness and reliability of AI systems across diverse applications, ranging from facial expression recognition and anomaly detection to medical image analysis and drug discovery, where data scarcity or domain shifts are common challenges. The ultimate goal is to build more adaptable and trustworthy AI systems.

Papers

September 15, 2024

Learning Transferable Features for Implicit Neural Representations
Kushal Vyas, Ahmed Imtiaz Humayun, Aniket Dashpute, Richard G. Baraniuk, Ashok Veeraraghavan, Guha Balakrishnan
Transferable Representation Encoder Layer Data Driven Prior Generalizable Feature Encoder Representation

August 20, 2024

Generalizable Facial Expression Recognition
Yuhang Zhang, Xiuqi Zheng, Chenyi Liang, Jiani Hu, Weihong Deng
Facial Expression Recognition Generalizable Feature Expression Representation Facial Affect Facial Expression Recognition Datasets

August 6, 2024

Diffusion Model Meets Non-Exemplar Class-Incremental Learning and Beyond
Jichuan Zhang, Yali Li, Xin Liu, Shengjin Wang
Diffusion Model Self Supervised Class Incremental Learning Class Specific Feature Generalizable Feature Memorized Knowledge

July 17, 2024

A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos
Sabah Abdulazeez Jebur, Khalid A. Hussein, Haider Kadhim Hoomod, Laith Alzubaidi, Ahmed Ali Saihood, YuanTong Gu
Neural Network Deep Learning Anomaly Detection Surveillance Video Violence Detection Generalizable Feature Package Theft

May 24, 2024

Unbiased Faster R-CNN for Single-source Domain Generalized Object Detection
Yajing Liu, Shijun Zhou, Xiyao Liu, Chunhui Hao, Baojie Fan, Jiandong Tian
Object Detection Domain Invariant Feature Faster R CNN Causal Attention Single Source Domain Generalization Generalizable Feature

April 9, 2024

GHNeRF: Learning Generalizable Human Features with Efficient Neural Radiance Fields
Arnab Dey, Di Yang, Rohith Agaram, Antitza Dantcheva, Andrew I. Comport, Srinath Sridhar, Jean Martinet
Neural Radiance Field 3D Human 3D Scene Representation Generalizable Feature

March 8, 2024

A Feature-based Generalizable Prediction Model for Both Perceptual and Abstract Reasoning
Quan Do, Thomas M. Morin, Chantal E. Stern, Michael E. Hasselmo
Symbolic Representation Abstract Reasoning Perceptual Understanding Modern Neural Network Generalizable Feature Progressive Matrix Continuous Image Representation Rule Abstraction

September 28, 2023

Rethinking Domain Generalization: Discriminability and Generalizability
Shaocong Long, Qianyu Zhou, Chenhao Ying, Lizhuang Ma, Yuan Luo
Stronger Generalizability Domain Invariant Representation Discriminative Task Generalizable Feature

September 27, 2023

Automatic Feature Fairness in Recommendation via Adversaries
Hengchang Hu, Yiming Cao, Zhankui He, Samson Tan, Min-Yen Kan
Adversarial Perturbation Effective Recommendation Adversary Agent Fairness Aware Generalizable Feature Space Bias Imbalanced Training

June 19, 2023

Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics
Kenta Oono, Nontawat Charoenphakdee, Kotatsu Bito, Zhengyan Gao, Hideyoshi Igata, Masashi Yoshikawa, Yoshiaki Ota, Hiroki Okui, Kei Akita, Shoichiro Yamaguchi, Yohei Sugawara, Shin-ichi Maeda, Kunihiko Miyoshi, Yuki Saito, Koki Tsuda, Hiroshi Maruyama, Kohei Hayashi
Machine Learning Model Deep Generative Model Generalizable Feature Virtual Measurement

February 28, 2023

DEff-GAN: Diverse Attribute Transfer for Few-Shot Image Synthesis
Rajiv Kumar, G. Sivakumar
GAN Model Image Synthesis C Gan Generalizable Feature Single GAN Efficient GAN

September 9, 2022

Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System
Xin Li, Yao Qiang, Chengyin Li, Sijia Liu, Dongxiao Zhu
Deep Neural Network Financial Application Adversarial Training Medical Image Classification Human Saliency Centralized Machine Learning Generalizable Feature

May 15, 2022

Uncertainty estimation for Cross-dataset performance in Trajectory prediction
Thomas Gilles, Stefano Sabatini, Dzmitry Tsishkou, Bogdan Stanciulescu, Fabien Moutarde
Trajectory Prediction Uncertainty Estimation Trajectory Prediction Model Prediction Uncertainty Cross Dataset Generalizable Feature State of the Art Trajectory

April 26, 2022

Improving Feature Generalizability with Multitask Learning in Class Incremental Learning
Dong Ma, Chi Ian Tang, Cecilia Mascolo
Incremental Learning Class Incremental Learning Multitask Learning Keyword Spotting Generalizable Feature

March 31, 2022

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks
Da-Wei Zhou, Han-Jia Ye, Liang Ma, Di Xie, Shiliang Pu, De-Chuan Zhan
Supervised Learning Class Incremental Learning Generalizable Feature Shot Class Class Prototype Multi Stage Task Learning Multi Phase Incremental Task

November 30, 2021

Molecular Attributes Transfer from Non-Parallel Data
Shuangjia Zheng, Ying Song, Zhang Pan, Chengtao Li, Le Song, Yuedong Yang
Generative Model Molecular Optimization Generalizable Feature Non Parallel