4.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Seoul National UniversityKR138 papers
- The University of TokyoJP133 papers
- Centre National de la Recherche ScientifiqueFR113 papers
- Pusan National UniversityKR110 papers
- Massachusetts Institute of TechnologyUS105 papers
- Korea Astronomy and Space Science InstituteKR104 papers
- California Institute of TechnologyUS99 papers
- Université Libre de BruxellesBE99 papers
- University of ChicagoUS99 papers
- National Astronomical Observatory of JapanJP97 papers
- Lomonosov Moscow State UniversityRU96 papers
- Universität HamburgDE94 papers
5 papers · 2 filters
Machine Learning Optimal Ordering in Global Routing Problems in Semiconductors
Heejin Choi, Minji Lee, Chang Hyeong Lee +2
In this work, we propose a new method for ordering nets during the process of layer assignment in global routing problems. The global routing problems that we focus on in this work…
SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization
Kwangryeol Park, Seulki Lee
We propose SMMF (Square-Matricized Momentum Factorization), a memory-efficient optimizer that reduces the memory requirement of the widely used adaptive learning rate optimizers, s…
Geodesic Flow Kernels for Semi-Supervised Learning on Mixed-Variable Tabular Dataset
Yoontae Hwang, Yongjae Lee
Tabular data poses unique challenges due to its heterogeneous nature, combining both continuous and categorical variables. Existing approaches often struggle to effectively capture…
CAFO: Feature-Centric Explanation on Time Series Classification
Jaeho Kim, Seok-Ju Hahn, Yoontae Hwang +2
In multivariate time series (MTS) classification, finding the important features (e.g., sensors) for model performance is crucial yet challenging due to the complex, high-dimension…
DualDynamics: Synergizing Implicit and Explicit Methods for Robust Irregular Time Series Analysis
YongKyung Oh, Dong-Young Lim, Sungil Kim
Real-world time series analysis faces significant challenges when dealing with irregular and incomplete data. While Neural Differential Equation (NDE) based methods have shown prom…