Rio Yokota
17 papers · 2019–2026 · 9 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
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πΊοΈ Taxonomy Completionist (34) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π Grand Slam
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Mega-Team Β· Squad
ποΈ
Keyword Collector
(72)
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Unstoppable Β· Bronze
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The Questioner
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Renaissance Researcher
(5)
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(11)
Artificial Intelligence
(8)
Deep Learning
(7)
Architectures
(6)
Optimization & Theory
(6)
Computer Vision
(4)
Application Areas
(4)
Core AI
(4)
Learning Paradigms
(4)
Natural Language Processing
(3)
Learning Types Β· Machine Learning
(3)
Resources & Methods
(3)
Analysis
(2)
Learning Types Β· Deep Learning
(2)
Techniques
(2)
Keywords
formula-driven supervised learning
(4)
vision transformer
(3)
synthetic image
(2)
image classification
(2)
distributed learning
(2)
neural network optimization
(2)
second-order optimization
(2)
formula-driven supervision
(2)
multilingual model
(2)
variational inference
(1)
code generation
(1)
cross-lingual transfer
(1)
continual learning
(1)
deep learning
(1)
data augmentation
(1)
self-supervised learning
(1)
semantic segmentation
(1)
continued pretraining
(1)
synthetic data generation
(1)
medical text
(1)
Papers
FedPM: Federated Learning Using Second-order Optimization with Preconditioned Mixing of Local Parameters
AAAI 2026
PowerCLIP: Powerset Alignment for Contrastive Pre-Training
CVPR 2026
Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code
COLING 2025
Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization
ICLR 2025
Leveraging High-Resource English Corpora for Cross-lingual Domain Adaptation in Low-Resource Japanese Medicine via Continued Pre-training
EMNLP 2025
Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
ICLR 2025
Formula-Supervised Visual-Geometric Pre-training
ECCV 2024
Rethinking Image Super Resolution from Training Data Perspectives
ECCV 2024
Scaling Backwards: Minimal Synthetic Pre-training?
ECCV 2024
Variational Learning is Effective for Large Deep Networks
ICML 2024
Pre-training Vision Transformers with Very Limited Synthesized Images
ICCV 2023
SegRCDB: Semantic Segmentation via Formula-Driven Supervised Learning
ICCV 2023
Visual Atoms: Pre-Training Vision Transformers With Sinusoidal Waves
CVPR 2023
Replacing Labeled Real-Image Datasets With Auto-Generated Contours
CVPR 2022
RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering
ICCV 2021
Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks
CVPR 2019
Practical Deep Learning with Bayesian Principles
NeurIPS 2019