머신러닝, 학회
ICML 논문을 낸 국내 연구실
탑티어International Conference on Machine Learning. 2023년 이후 논문 284편, 연구실 148곳
이 학회에 논문을 낸 연구실
| 연구실 | 대학 | 탑티어 논문 | 전체 논문 | 구성원 | 비교 |
|---|---|---|---|---|---|
 MLCF김하영 교수신생 랩모집 안내 | 연세대 | 10 | 23 | 27 | |
 PRISM Lab정형진 교수신생 랩모집 안내 | 고려대 | 22 | 25 | 4 | |
 SNU GSDS Lee Lab이승근 교수 | 서울대 | 1 | 6 | – | |
 Ubiquitous AI Lab. 유비쿼터스 인공지능 연구실공태식 교수신생 랩모집 안내 | UNIST | 13 | 21 | 5 | |
 Users and Information Lab오혜연 교수 | KAIST | 33 | 45 | – | |
 Vision & AI Lab이정범 교수신생 랩모집 안내 | 고려대 | 8 | 9 | 21 | |
 Visual Information Processing Lab이준석 교수모집 안내 | 서울대 | 26 | 40 | 58 | |
 Visual intelligence어영정 교수 | 연세대 | 22 | 26 | – |
최근 논문
- DevFormer: A Symmetric Transformer for Context-Aware Device Placement
2023, System Intelligence Lab
- Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation
2023, Inference and Information for Data Science Lab
- Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming
2023, 머신러닝 연구실
- EM-Network: Oracle Guided Self-distillation for Sequence Learning
2023, 휴먼인터페이스연구실
- End-to-End Multi-Object Detection with a Regularized Mixture Model
2023, MIPA Laboratory
- Exploring Chemical Space with Score-based Out-of-distribution Generation
2023, 황성주 연구실
- Exploring the Benefits of Training Expert Language Models over Instruction Tuning
2023, 서민준 연구실
- Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
2023, 양은호 연구실
- GeCoNeRF: Few-shot Neural Radiance Fields via Geometric Consistency
2023, 김승룡 연구실
- GREAD: Graph Neural Reaction-Diffusion Networks
2023, 소프트컴퓨팅, 빅데이터 분석 및 학습 연구실
- Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive Analysis
2023, 최적화및응용
- Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples
2023, IDEA Lab
- Improving Fair Training under Correlation Shifts
2023, 데이터 지능 연구실, 정보 시스템 연구실
- Improving Visual Prompt Tuning for Self-supervised Vision Transformers
2023, 인공지능 연구실, Vision & AI Lab
- Information-Theoretic State Space Model for Multi-View Reinforcement Learning
2023, 비전 및 학습 연구실, KAIST AIPR Lab, AI Cognition Optimization with Reinforcement & Exploration (AI-CORE) Lab. 지능 최적화 및 강화학습 연구실
- InGram: Inductive Knowledge Graph Embedding via Relation Graphs
2023, 빅데이터 지능 연구실
- KDEformer: Accelerating Transformers via Kernel Density Estimation
2023, 한인수 연구실
- Learning Affinity with Hyperbolic Representation for Spatial Propagation
2023, 시각인공지능
- Learning Controllable Degradation for Real-World Super-Resolution via Constrained Flows
2023, 시각지능 연구실, 백성용 연구실
- Learning to Boost Training by Periodic Nowcasting Near Future Weights
2023, Medical Information Processing Lab, Medical Information Processing Lab