Miao Xu
24 papers · 2013–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Conference Polyglot (7) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (12) π Academic Marathon (12)
π
Academic Marathon
(12)
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Cross-Pollinator
(10)
π
Renaissance Researcher
(7)
π¬
Deep Specialist
(10)
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Keyword Champion
(2)
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Grand Slam
π
Conference Pioneer
π
Trend Setter
β
The Questioner
π
Century Club
(23)
ποΈ
Keyword Collector
(95)
π₯
Unstoppable
(9)
β‘
Prolific Year
(5)
Conferences
IJCAI (6)
NIPS (6)
ICML (5)
AAAI (3)
ACL (1)
ACML (1)
ICLR (1)
MICCAI (1)
Top co-authors
Research topics
Keywords
weakly supervised learning
(3)
machine unlearning
(3)
partial-label learning
(3)
label noise
(3)
matrix completion
(2)
risk estimation
(2)
unbiased risk estimator
(2)
noisy label
(2)
model forgetting
(2)
binary classification
(2)
multi-class classification
(2)
positive-unlabeled learning
(2)
data-free learning
(1)
multi-label learning
(1)
sample complexity
(1)
multi-label classification
(1)
transductive learning
(1)
representation learning
(1)
low-rank approximation
(1)
knowledge distillation
(1)
Papers
VideoStir: Understanding Long Videos via Spatio-Temporally Structured and Intent-Aware RAG
ACL 2026
Reconstructing 3D Hand-Instrument Interaction from a Single 2D Image in Medical Scenes
MICCAI 2025
Toward Efficient Data-Free Unlearning
AAAI 2025
Inspecting Prediction Confidence for Detecting Black-Box Backdoor Attacks
AAAI 2024
What Makes Partial-Label Learning Algorithms Effective?
NIPS 2024
Countering Relearning with Perception Revising Unlearning
ACML 2024
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
ICLR 2024
Machine Unlearning: Challenges in Data Quality and Access
IJCAI 2024
Unlearning from Weakly Supervised Learning
IJCAI 2024
Unbiased Risk Estimator to Multi-Labeled Complementary Label Learning
IJCAI 2023
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization
NIPS 2022
Self-Supervised Adversarial Distribution Regularization for Medication Recommendation
IJCAI 2021
Pointwise Binary Classification with Pairwise Confidence Comparisons
ICML 2021
Positive-Unlabeled Learning from Imbalanced Data
IJCAI 2021
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
ICML 2020
Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering
NIPS 2020
Provably Consistent Partial-Label Learning
NIPS 2020
Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
ICML 2020
Progressive Identification of True Labels for Partial-Label Learning
ICML 2020
Clipped Matrix Completion: A Remedy for Ceiling Effects
AAAI 2019
Co-teaching: Robust training of deep neural networks with extremely noisy labels
NIPS 2018
Incomplete Label Distribution Learning
IJCAI 2017
CUR Algorithm for Partially Observed Matrices
ICML 2015
Speedup Matrix Completion with Side Information: Application to Multi-Label Learning
NIPS 2013