Yasutoshi Ida
14 papers · 2017–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (8) π§ Keyword Pioneer π Interdisciplinary Bridge π Conference Polyglot (5) π Cross-Pollinator (13)
π
Academic Marathon
(8)
π§
Keyword Pioneer
ποΈ
Keyword Collector
(62)
π
Century Club
(14)
π₯
Unstoppable
(7)
π
Trend Setter
π
Conference Pioneer
Conferences
NIPS (5)
AAAI (4)
AISTATS (2)
ICML (2)
IJCAI (1)
Top co-authors
Keywords
feature selection
(4)
sparse optimization
(3)
neural network
(3)
adversarial training
(2)
few-shot learning
(2)
block coordinate descent
(2)
covariance matrix
(1)
compressive sensing
(1)
adversarial robustness
(1)
unsupervised domain adaptation
(1)
network pruning
(1)
low-rank approximation
(1)
non-convex optimization
(1)
sparse regression
(1)
sparse regularization
(1)
optimal transport
(1)
hilbert-schmidt independence criterion
(1)
coordinate descent
(1)
sparsity-inducing norms
(1)
gradient descent
(1)
Papers
Meta-learning Task-specific Regularization Weights for Few-shot Linear Regression
AISTATS 2025
Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations
NIPS 2024
Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers
AAAI 2023
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training
ICML 2023
Fast Block Coordinate Descent for Non-Convex Group Regularizations
AISTATS 2023
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks
AAAI 2023
Meta-ticket: Finding optimal subnetworks for few-shot learning within randomly initialized neural networks
NIPS 2022
Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion
NIPS 2022
Pruning Randomly Initialized Neural Networks with Iterative Randomization
NIPS 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
Fast Sparse Group Lasso
NIPS 2019
Efficient Data Point Pruning for One-Class SVM
AAAI 2019
Adaptive Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks
IJCAI 2017