Ikko Yamane
9 papers · 2016–2024 · 6 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (28) 🐣 Hot Topic Early Bird
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Research topics
Machine Learning
(9)
Learning Types
(7)
Optimization & Theory · Machine Learning
(6)
Application Areas
(4)
Core Methods
(4)
Artificial Intelligence
(1)
Data Science & Analytics
(1)
Deep Learning
(1)
Mathematics & Optimization
(1)
Applications
(1)
Bayesian & Probabilistic
(1)
Core AI
(1)
Learning Paradigms
(1)
Optimization
(1)
Optimization & Theory · Deep Learning
(1)
Keywords
covariate shift
(2)
domain adaptation
(2)
transfer learning
(2)
double descent
(1)
binary classification
(1)
continuous optimization
(1)
statistical consistency
(1)
convex optimization
(1)
principal component analysis
(1)
function approximation
(1)
model evaluation
(1)
supervised learning
(1)
bregman divergence
(1)
empirical risk minimization
(1)
bayes error
(1)
multi-task learning
(1)
nearest neighbor
(1)
dimensionality reduction
(1)
importance weighting
(1)
causal inference
(1)
Papers
Nearest Neighbor Sampling for Covariate Shift Adaptation
JMLR 2024
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification
ICLR 2023
Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality
AISTATS 2023
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
ICML 2021
Skew-symmetrically perturbed gradient flow for convex optimization
ACML 2021
A One-step Approach to Covariate Shift Adaptation
ACML 2020
Do We Need Zero Training Loss After Achieving Zero Training Error?
ICML 2020
Uplift Modeling from Separate Labels
NeurIPS 2018
Multitask Principal Component Analysis
ACML 2016