Feng Hong
11 papers · 2020–2026 · 8 venues · across top CS/AI venues
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Research topics
Machine Learning
(8)
Learning Types Β· Machine Learning
(5)
Artificial Intelligence
(4)
Deep Learning
(4)
Core Methods
(4)
Core AI
(3)
Learning Types Β· Deep Learning
(3)
Natural Language Processing
(2)
Optimization & Theory
(2)
Data Science & Analytics
(1)
Knowledge & Reasoning
(1)
Application Areas
(1)
Applications
(1)
Generation
(1)
Learning Paradigms
(1)
Keywords
self-supervised learning
(2)
imbalanced learning
(2)
deep learning
(2)
contrastive learning
(1)
causal reasoning
(1)
text classification
(1)
domain adaptation
(1)
time series forecasting
(1)
multimodal learning
(1)
structure extraction
(1)
density ratio estimation
(1)
neural network optimization
(1)
label disambiguation
(1)
class imbalance
(1)
partial label learning
(1)
model calibration
(1)
few-shot learning
(1)
batch selection
(1)
causal knowledge
(1)
sequence modeling
(1)
Papers
Rejection Mixing: Fast Semantic Propagation of Mask Tokens for Efficient DLLM Inference
CVPR 2026
Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning
ICCV 2025
Non-collective Calibrating Strategy for Time Series Forecasting
IJCAI 2025
Diversified Batch Selection for Training Acceleration
ICML 2024
On Harmonizing Implicit Subpopulations
ICLR 2024
Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation
NeurIPS 2024
Combating Representation Learning Disparity with Geometric Harmonization
NeurIPS 2023
Long-Tailed Partial Label Learning via Dynamic Rebalancing
ICLR 2023
A Bottom-Up DAG Structure Extraction Model for Math Word Problems
AAAI 2021
Learning to Learn Personalized Neural Network for Ventricular Arrhythmias Detection on Intracardiac EGMs
IJCAI 2021
Ferryman as SemEval-2020 Task 5: Optimized BERT for Detecting Counterfactuals
SemEval 2020