Long-Kai Huang

26 papers · 2013–2025 · 6 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🌍 Conference Polyglot (6) 🏃 Academic Marathon (12) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (7)

🧭 Keyword Pioneer 🐝 Cross-Pollinator (7) 🏆 Grand Slam 👑 Triple Crown 🤝 Dynamic Duo (11) 🔥 Unstoppable (7) 💎 Century Club (26) 🚀 Conference Pioneer 🗃️ Keyword Collector (67) ⚡ Prolific Year (5)

Conferences

NIPS (7) ICML (6) ICLR (5) IJCAI (4) AAAI (2) ICCV (2)

Top co-authors

Ying Wei (11) Junzhou Huang (5) Yu Rong (5) Yichen WU (4) Peilin Zhao (4) Sinno Jialin Pan (3) Bingzhe Wu (3) Qiang Yang (3) Yunqiao Yang (2) Sinno Pan (2)

Keywords

transfer learning (4) few-shot learning (3) domain generalization (3) knowledge transfer (2) feature representation (2) optimal transport (2) task augmentation (2) mutual information (2) drug discovery (2) graph neural network (2) image retrieval (1) object recognition (1) feature learning (1) representation learning (1) principal component analysis (1) domain adaptation (1) vision transformer (1) deep hashing (1) gradient attention (1) adversarial training (1)

Papers

Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization ICLR 2025 IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck ICML 2025 Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model AAAI 2025 Steering Protein Language Models ICML 2025 Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation ICLR 2025 SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning ICLR 2025 Learning Where to Edit Vision Transformers NIPS 2024 Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction ICLR 2024 Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time ICLR 2024 Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization ICML 2024 Towards Understanding Evolving Patterns in Sequential Data NIPS 2024 DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations AAAI 2023 Secure Out-of-Distribution Task Generalization with Energy-Based Models NIPS 2023 Retaining Beneficial Information from Detrimental Data for Neural Network Repair NIPS 2023 Concept-wise Fine-tuning Matters in Preventing Negative Transfer ICCV 2023 Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport IJCAI 2022 Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization NIPS 2022 Adversarial Task Up-sampling for Meta-learning NIPS 2022 Frustratingly Easy Transferability Estimation ICML 2022 Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery NIPS 2021 Improving Generalization in Meta-learning via Task Augmentation ICML 2021 Communication-Efficient Distributed PCA by Riemannian Optimization ICML 2020 Accelerate Learning of Deep Hashing With Gradient Attention ICCV 2019 Class-Wise Supervised Hashing with Label Embedding and Active Bits IJCAI 2016 Online Hashing IJCAI 2013 Smart Hashing Update for Fast Response IJCAI 2013