← Authors

Andrew Y. Ng

45 papers · 2003–2024 · 13 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (30) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (13) 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (21) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (10) 🏠 Conference Loyalist (21) 🌟 Keyword Trendsetter Combo (10) 🌱 Topic Pioneer πŸ† Keyword Champion (3) πŸ”¬ Deep Specialist (10) πŸ‘₯ Mega-Team (47) πŸ—ƒοΈ Keyword Collector (131) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ⚑ Prolific Year (7) πŸ’Ž Century Club (45) πŸ”₯ Unstoppable (5)

Conferences

NIPS (21) MIDL (5) EMNLP (4) ACL (3) CONLL (2) JMLR (2) MLHC (2) AAAI (1) COLING (1) CVPR (1) ICLR (1) RSS (1) UAI (1)

Top co-authors

Christopher D. Manning (7) Pranav Rajpurkar (7) Richard Socher (6) Quoc V Le (4) Rion Snow (4) Honglak Lee (4) Daniel Jurafsky (4) Pieter Abbeel (4) Adam Coates (4) Quoc V. Le (4)

Research topics

Core AI (2) Robotics (1)

Keywords

feature learning (12) unsupervised learning (7) unsupervised feature learning (6) representation learning (6) convolutional neural network (5) chest x-ray (5) computer vision (4) image classification (3) sparse coding (3) hierarchical feature (3) hierarchical feature learning (2) deep learning (2) contrastive learning (2) feature representation (2) medical imaging (2) object detection (2) structured prediction (2) reinforcement learning (2) feature extraction (2) hierarchical learning (2)

Papers

Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation MIDL 2024
DataPerf: Benchmarks for Data-Centric AI Development NIPS 2023
MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning MIDL 2022
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models MIDL 2021
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation MLHC 2021
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays MLHC 2021
Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays MIDL 2021
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation MIDL 2021
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology ICLR 2021
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison AAAI 2019
Countdown Regression: Sharp and Calibrated Survival Predictions UAI 2019
End-To-End People Detection in Crowded Scenes CVPR 2016
Parsing with Compositional Vector Grammars ACL 2013
Emergence of Object-Selective Features in Unsupervised Feature Learning NIPS 2012
Deep Learning of Invariant Features via Simulated Fixations in Video NIPS 2012
Convolutional-Recursive Deep Learning for 3D Object Classification NIPS 2012
Large Scale Distributed Deep Networks NIPS 2012
Semantic Compositionality through Recursive Matrix-Vector Spaces CONLL 2012
Semantic Compositionality through Recursive Matrix-Vector Spaces EMNLP 2012
Sparse Filtering NIPS 2011
Selecting Receptive Fields in Deep Networks NIPS 2011
ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning NIPS 2011
Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection NIPS 2011
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions EMNLP 2011
Learning Word Vectors for Sentiment Analysis ACL 2011
Unsupervised learning models of primary cortical receptive fields and receptive field plasticity NIPS 2011
Energy Disaggregation via Discriminative Sparse Coding NIPS 2010
Tiled convolutional neural networks NIPS 2010
Unsupervised feature learning for audio classification using convolutional deep belief networks NIPS 2009
Measuring Invariances in Deep Networks NIPS 2009
Learning to Merge Word Senses CONLL 2007
Learning to Merge Word Senses EMNLP 2007
Sparse deep belief net model for visual area V2 NIPS 2007
Efficient multiple hyperparameter learning for log-linear models NIPS 2007
Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion NIPS 2007
An Application of Reinforcement Learning to Aerobatic Helicopter Flight NIPS 2006
Semantic Taxonomy Induction from Heterogenous Evidence ACL 2006
Semantic Taxonomy Induction from Heterogenous Evidence COLING 2006
Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines EMNLP 2006
Efficient sparse coding algorithms NIPS 2006
Learning Factor Graphs in Polynomial Time and Sample Complexity JMLR 2006
Robotic Grasping of Novel Objects NIPS 2006
Map-Reduce for Machine Learning on Multicore NIPS 2006
Discriminative Training of Kalman Filters RSS 2005
Latent Dirichlet Allocation JMLR 2003