Yasutoshi Ida
14 papers · 2017–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+5 more ↓ Show less ↑
🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (29)
🧭
Keyword Pioneer
🗃️
Keyword Collector
(64)
💎
Century Club · Bronze
🔥
Unstoppable · Bronze
🚀
Conference Pioneer
Top co-authors
Research topics
Machine Learning
(12)
Optimization & Theory · Machine Learning
(9)
Core Methods
(6)
Deep Learning
(5)
Mathematics & Optimization
(5)
Learning Types · Machine Learning
(5)
Optimization
(5)
Artificial Intelligence
(4)
Architectures
(4)
Learning Types · Deep Learning
(3)
Core AI
(2)
Learning Paradigms
(2)
Optimization & Theory · Deep Learning
(2)
Computer Vision
(1)
Application Areas
(1)
Keywords
feature selection
(4)
few-shot learning
(3)
neural network
(3)
sparse optimization
(3)
block coordinate descent
(2)
linear regression
(2)
adversarial training
(2)
covariance matrix
(1)
compressive sensing
(1)
adversarial robustness
(1)
unsupervised domain adaptation
(1)
low-rank approximation
(1)
network pruning
(1)
sparse regression
(1)
non-convex optimization
(1)
coordinate descent
(1)
sparse regularization
(1)
optimal transport
(1)
sparsity-inducing norms
(1)
hilbert-schmidt independence criterion
(1)
Papers
Meta-learning Task-specific Regularization Weights for Few-shot Linear Regression
AISTATS 2025
Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations
NeurIPS 2024
Fast Block Coordinate Descent for Non-Convex Group Regularizations
AISTATS 2023
Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers
AAAI 2023
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks
AAAI 2023
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training
ICML 2023
Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion
NeurIPS 2022
Meta-ticket: Finding optimal subnetworks for few-shot learning within randomly initialized neural networks
NeurIPS 2022
Pruning Randomly Initialized Neural Networks with Iterative Randomization
NeurIPS 2021
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks
AAAI 2020
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance
ICML 2020
Efficient Data Point Pruning for One-Class SVM
AAAI 2019
Fast Sparse Group Lasso
NeurIPS 2019
Adaptive Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks
IJCAI 2017