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Junbin Gao

25 papers · 2014–2025 · 10 conferences · across top CS/AI conferences

Achievements

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+9 more ↓ πŸƒ Academic Marathon (11) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (10) 🐝 Cross-Pollinator (8)
🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (45) πŸ† Grand Slam πŸ† Keyword Champion (3) πŸ’Ž Century Club (25) πŸ—ƒοΈ Keyword Collector (110) πŸ”₯ Unstoppable (12) πŸ“ˆ Trend Setter

Conferences

CVPR (8) AAAI (4) IJCAI (4) ICLR (2) ICML (2) ACL (1) AISTATS (1) ICCV (1) NAACL (1) NIPS (1)

Top co-authors

Baocai Yin (7) Yanfeng Sun (6) Yongli Hu (6) Andi Han (5) Zhiyong Wang (4) Yi Guo (3) Dai Shi (2) Ming Yin (2) Anton van den Hengel (2) Fujiao Ju (2)

Keywords

riemannian optimization (4) subspace clustering (4) dimensionality reduction (4) low-rank representation (4) low rank representation (3) sparse representation (3) grassmann manifold (3) graph neural network (2) matrix factorization (2) multi-label classification (2) positive definite matrix (2) variational inference (1) spectral clustering (1) feature extraction (1) manifold learning (1) stochastic gradient (1) non-convex optimization (1) robust regression (1) convergence acceleration (1) subspace learning (1)

Papers

When Graph Neural Networks Meet Dynamic Mode Decomposition ICLR 2025 Language-Driven Multi-Label Zero-Shot Learning with Semantic Granularity ICCV 2025 HC-LLM: Historical-Constrained Large Language Models for Radiology Report Generation AAAI 2025 Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning ICLR 2025 Diffusion Models Demand Contrastive Guidance for Adversarial Purification to Advance ICML 2024 Graph Neural Networks with Soft Association between Topology and Attribute AAAI 2024 Efficient and Interpretable Compressive Text Summarisation with Unsupervised Dual-Agent Reinforcement Learning ACL 2023 Riemannian Accelerated Gradient Methods via Extrapolation AISTATS 2023 OTExtSum: Extractive Text Summarisation with Optimal Transport NAACL 2022 On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry NIPS 2021 Hierarchical Graph Convolution Network for Traffic Forecasting AAAI 2021 How Framelets Enhance Graph Neural Networks ICML 2021 Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization IJCAI 2021 Shared Generative Latent Representation Learning for Multi-View Clustering AAAI 2020 Hype-HAN: Hyperbolic Hierarchical Attention Network for Semantic Embedding IJCAI 2020 Double Nuclear Norm Based Low Rank Representation on Grassmann Manifolds for Clustering CVPR 2019 Cascaded Low Rank and Sparse Representation on Grassmann Manifolds IJCAI 2018 Low-Rank-Sparse Subspace Representation for Robust Regression CVPR 2017 Locality Preserving Projections for Grassmann manifold IJCAI 2017 Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering CVPR 2017 Proximal Riemannian Pursuit for Large-Scale Trace-Norm Minimization CVPR 2016 Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis CVPR 2016 Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds CVPR 2016 Learning Graph Structure for Multi-Label Image Classification via Clique Generation CVPR 2015 Subspace Clustering for Sequential Data CVPR 2014