Paper "representation learning" Papers
20 papers found
Conference
ACCon: Angle-Compensated Contrastive Regularizer for Deep Regression
Botao Zhao, Xiaoyang Qu, Zuheng Kang et al.
Contrastive Representation for Interactive Recommendation
Jingyu Li, Zhiyong Feng, Dongxiao He et al.
Deep Representation Learning for Forecasting Recursive and Multi-Relational Events in Temporal Networks
Tony Gracious, Ambedkar Dukkipati
DELTA: Pre-Train a Discriminative Encoder for Legal Case Retrieval via Structural Word Alignment
Haitao Li, Qingyao Ai, Xinyan Han et al.
Enhancing Masked Time-Series Modeling via Dropping Patches
Tianyu Qiu, Yi Xie, Hao Niu et al.
FCOM: A Federated Collaborative Online Monitoring Framework via Representation Learning
Tanapol Kosolwattana, Huazheng Wang, Raed Al Kontar et al.
Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales
Xinyu Yang, Yu Sun, Xinyang Chen et al.
Parallel-Learning of Invariant and Tempo-variant Attributes of Single-Lead Cardiac Signals: PLITA
Adrian Atienza, Jakob E. Bardram, Sadasivan Puthusserypady
Prior-Constrained Association Learning for Fine-Grained Generalized Category Discovery
Menglin Wang, Zhun Zhong, Xiaojin Gong
Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control
Bruce D. Lee, Leonardo F. Toso, Thomas T. Zhang et al.
Structural Entropy Guided Probabilistic Coding
Xiang Huang, Hao Peng, Li Sun et al.
Adaptive Discovering and Merging for Incremental Novel Class Discovery
Guangyao Chen, Peixi Peng, Yangru Huang et al.
BaCon: Boosting Imbalanced Semi-supervised Learning via Balanced Feature-Level Contrastive Learning
Qianhan Feng, Lujing Xie, Shijie Fang et al.
Beyond Prototypes: Semantic Anchor Regularization for Better Representation Learning
Yanqi Ge, Qiang Nie, Ye Huang et al.
Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation
Jiyong Li, Dilshod Azizov, Yang LI et al.
Exploring Diverse Representations for Open Set Recognition
Yu Wang, Junxian Mu, Pengfei Zhu et al.
Neural Causal Abstractions
Kevin Xia, Elias Bareinboim
Non-parametric Representation Learning with Kernels
Hebaixu Wang, Meiqi Gong, Xiaoguang Mei et al.
Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning
Ruiqian Nai, Zixin Wen, Ji Li et al.
Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data
Shuvendu Roy, Ali Etemad