← Authors

Akiko Takeda

23 papers · 2012–2025 · 8 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (13) 🐝 Cross-Pollinator (6) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌱 Topic Pioneer πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (86) πŸ’Ž Century Club (23) πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter ⚑ Prolific Year (5)

Conferences

NIPS (7) ICML (5) JMLR (5) AISTATS (2) AAAI (1) COLT (1) ICLR (1) UAI (1)

Top co-authors

Andi Han (4) Taiji Suzuki (4) Wei Huang (2) Michael R. Metel (2) Junpei Komiyama (2) Pierre-Louis Poirion (2) Pratik Jawanpuria (2) Takafumi Kanamori (2) Bamdev Mishra (2) Junya Honda (2)

Keywords

binary classification (4) stochastic optimization (4) support vector machine (4) global optimization (3) non-convex optimization (3) bilevel optimization (3) nonconvex optimization (2) gradient descent (2) uncertainty set (2) homotopy method (2) proximal gradient method (2) hyperparameter learning (2) outlier detection (2) bayesian learning (1) variational inference (1) data poisoning (1) statistical consistency (1) stochastic gradient (1) single-loop optimization (1) parameter estimation (1)

Papers

Zeroth-Order Methods for Nonconvex Stochastic Problems with Decision-Dependent Distributions AAAI 2025
Modified K-means Algorithm with Local Optimality Guarantees ICML 2025
Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold Method ICML 2025
On the Role of Label Noise in the Feature Learning Process ICML 2025
Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization ICLR 2025
A Framework for Bilevel Optimization on Riemannian Manifolds NIPS 2024
SLTrain: a sparse plus low rank approach for parameter and memory efficient pretraining NIPS 2024
Robust Gaussian process regression with the trimmed marginal likelihood UAI 2023
Single Loop Gaussian Homotopy Method for Non-convex Optimization NIPS 2022
A Gradient Method for Multilevel Optimization NIPS 2021
Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization JMLR 2021
On lp-hyperparameter Learning via Bilevel Nonsmooth Optimization JMLR 2021
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization ICML 2019
Nonconvex Optimization for Regression with Fairness Constraints ICML 2018
A Unified Formulation and Fast Accelerated Proximal Gradient Method for Classification JMLR 2017
Trimmed Density Ratio Estimation NIPS 2017
Position-based Multiple-play Bandit Problem with Unknown Position Bias NIPS 2017
Robust Cost Sensitive Support Vector Machine AISTATS 2015
Geometric Intuition and Algorithms for Ev--SVM JMLR 2015
Global Optimization Methods for Extended Fisher Discriminant Analysis AISTATS 2014
Conjugate Relation between Loss Functions and Uncertainty Sets in Classification Problems JMLR 2013
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering NIPS 2013
A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems COLT 2012