Atsushi Nitanda
33 papers · 2014–2025 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+13 more ↓ Show less ↑
π§ Keyword Pioneer π£ Hot Topic Early Bird π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (10) π Conference Polyglot (5)
π
Conference Polyglot
(5)
π
Cross-Pollinator
(8)
πΊ
Lone Wolf
(3)
π±
Topic Pioneer
π
Triple Crown
π
Keyword Champion
(2)
π€
Dynamic Duo
(25)
ποΈ
Keyword Collector
(107)
β
The Questioner
(2)
β‘
Prolific Year
(7)
π
Century Club
(33)
π₯
Unstoppable
(10)
π
Trend Setter
Conferences
NIPS (10)
AISTATS (9)
ICLR (7)
ICML (6)
ACML (1)
Top co-authors
Keywords
stochastic gradient descent
(7)
neural network
(5)
neural network optimization
(5)
hyperbolic space
(4)
variance reduction
(3)
exponential convergence
(3)
gradient boosting
(3)
ordinal embedding
(2)
functional gradient
(2)
mean-field langevin dynamics
(2)
generalization error bound
(2)
convex optimization
(2)
binary classification
(2)
residual network
(2)
convergence analysis
(2)
graph embedding
(2)
global convergence
(2)
gradient descent
(2)
stochastic optimization
(2)
propagation of chao
(2)
Papers
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
ICML 2025
Provable In-Context Vector Arithmetic via Retrieving Task Concepts
ICML 2025
Clustered Invariant Risk Minimization
AISTATS 2025
Direct Distributional Optimization for Provable Alignment of Diffusion Models
ICLR 2025
Improved Particle Approximation Error for Mean Field Neural Networks
NIPS 2024
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning
NIPS 2024
Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data
ICLR 2024
Koopman-based generalization bound: New aspect for full-rank weights
ICLR 2024
Why is parameter averaging beneficial in SGD? An objective smoothing perspective
AISTATS 2024
Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics
ICLR 2023
Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction
NIPS 2023
Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond
NIPS 2023
Tight and fast generalization error bound of graph embedding in metric space
ICML 2023
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems
ICML 2023
Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization
ICLR 2022
Two-layer neural network on infinite dimensional data: global optimization guarantee in the mean-field regime
NIPS 2022
Convex Analysis of the Mean Field Langevin Dynamics
AISTATS 2022
Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features
AISTATS 2021
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic
NIPS 2021
Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space
NIPS 2021
Particle Dual Averaging: Optimization of Mean Field Neural Network with Global Convergence Rate Analysis
NIPS 2021
When does preconditioning help or hurt generalization?
ICLR 2021
Optimal Rates for Averaged Stochastic Gradient Descent under Neural Tangent Kernel Regime
ICLR 2021
Generalization Error Bound for Hyperbolic Ordinal Embedding
ICML 2021
Functional Gradient Boosting for Learning Residual-like Networks with Statistical Guarantees
AISTATS 2020
Stochastic Gradient Descent with Exponential Convergence Rates of Expected Classification Errors
AISTATS 2019
Data Cleansing for Models Trained with SGD
NIPS 2019
Hyperbolic Ordinal Embedding
ACML 2019
Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models
AISTATS 2018
Functional Gradient Boosting based on Residual Network Perception
ICML 2018
Stochastic Difference of Convex Algorithm and its Application to Training Deep Boltzmann Machines
AISTATS 2017
Accelerated Stochastic Gradient Descent for Minimizing Finite Sums
AISTATS 2016
Stochastic Proximal Gradient Descent with Acceleration Techniques
NIPS 2014