大学 × Machine Learning
九州工業大学
Machine Learning / 2021–2025 確定版
掲載論文 13 本
論文一覧
13 本
このEditionのランキングに掲載している論文です。同じ大学の複数著者による共著は1本にまとめています。
ランキングの対象論文 13 本と一致しています。
2025年
- Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
掲載ID:
pmlr:v267:nitanda25a - Statistical Analysis of the Sinkhorn Iterations for Two-Sample Schr\"{o}dinger Bridge Estimation
掲載ID:
neurips:2025:ac22a9988f386be16d1d4b533ccc1af4
2023年
- Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics
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openreview:_jscuk9tbun - Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems
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pmlr:v202:nitanda23a - Tight and fast generalization error bound of graph embedding in metric space
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pmlr:v202:suzuki23a
2022年
- Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization
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iclr:2022:1597d21403f63da1bb0539592597a525 - Two-layer neural network on infinite dimensional data: global optimization guarantee in the mean-field regime
掲載ID:
neurips:2022:d2155b1f7eb42350d7bc3013eefe5480
2021年
- Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
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openreview:pulsd5qi2n1 - When does preconditioning help or hurt generalization?
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openreview:s724o4_wb3 - Generalization Error Bound for Hyperbolic Ordinal Embedding
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pmlr:v139:suzuki21a - Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space
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neurips:2021:1dacb10f0623c67cb7dbb37587d8b38a - Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic
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neurips:2021:09779bb7930c8a0a44360e12b538ae3c - Particle Dual Averaging: Optimization of Mean Field Neural Network with Global Convergence Rate Analysis
掲載ID:
neurips:2021:a34e1ddbb4d329167f50992ba59fe45a
掲載対象外の論文や未反映の論文は、この一覧には含まれません。