Atsushi Nitanda
According to our database1,
Atsushi Nitanda
authored at least 39 papers
between 2014 and 2024.
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Bibliography
2024
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning.
CoRR, 2024
Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
Convergence of mean-field Langevin dynamics: Time and space discretization, stochastic gradient, and variance reduction.
CoRR, 2023
CoRR, 2023
Koopman-Based Bound for Generalization: New Aspect of Neural Networks Regarding Nonlinear Noise Filtering.
CoRR, 2023
Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Mean-field Langevin dynamics: Time-space discretization, stochastic gradient, and variance reduction.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
Two-layer neural network on infinite dimensional data: global optimization guarantee in the mean-field regime.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Sharp characterization of optimal minibatch size for stochastic finite sum convex optimization.
Knowl. Inf. Syst., 2021
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Particle Dual Averaging: Optimization of Mean Field Neural Network with Global Convergence Rate Analysis.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime.
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Particle Dual Averaging: Optimization of Mean Field Neural Networks with Global Convergence Rate Analysis.
CoRR, 2020
A Novel Global Spatial Attention Mechanism in Convolutional Neural Network for Medical Image Classification.
CoRR, 2020
Functional Gradient Boosting for Learning Residual-like Networks with Statistical Guarantees.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Refined Generalization Analysis of Gradient Descent for Over-parameterized Two-layer Neural Networks with Smooth Activations on Classification Problems.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Stochastic Gradient Descent with Exponential Convergence Rates of Expected Classification Errors.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Proceedings of The 11th Asian Conference on Machine Learning, 2019
2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Stochastic Difference of Convex Algorithm and its Application to Training Deep Boltzmann Machines.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014