Jeff Z. HaoChen
9 papers · 2021–2023 · 5 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Silver
🌉
Interdisciplinary Bridge · Bronze
🗺️
Taxonomy Completionist
(25)
🐣
Hot Topic Early Bird
👑
Triple Crown
Venues
Top co-authors
Research topics
Machine Learning
(9)
Learning Types · Machine Learning
(7)
Optimization & Theory · Machine Learning
(4)
Deep Learning
(3)
Application Areas
(3)
Artificial Intelligence
(2)
Core AI
(2)
Core Methods
(2)
Optimization & Theory · Deep Learning
(2)
Natural Language Processing
(1)
Learning Types · Deep Learning
(1)
Models
(1)
Resources & Methods
(1)
Understanding
(1)
Keywords
contrastive learning
(5)
representation learning
(5)
self-supervised learning
(3)
unsupervised domain adaptation
(2)
feature disentanglement
(1)
domain adaptation
(1)
feature learning
(1)
multimodal learning
(1)
stochastic gradient descent
(1)
learning rate
(1)
spectral decomposition
(1)
class imbalance
(1)
error detection
(1)
label noise
(1)
natural language
(1)
question answering
(1)
stochastic gradient
(1)
inductive bia
(1)
implicit regularization
(1)
unsupervised learning
(1)
Papers
A theoretical study of inductive biases in contrastive learning
ICLR 2023
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models
ACL 2023
Diagnosing and Rectifying Vision Models using Language
ICLR 2023
Amortized Proximal Optimization
NeurIPS 2022
Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations
NeurIPS 2022
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation
ICML 2022
Self-supervised Learning is More Robust to Dataset Imbalance
ICLR 2022
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
NeurIPS 2021
Shape Matters: Understanding the Implicit Bias of the Noise Covariance
COLT 2021