Eric P Xing
24 papers · 2013–2019 · 2 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Renaissance Researcher (6) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (15) π£ Hot Topic Early Bird
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Cross-Pollinator
(14)
πΊοΈ
Taxonomy Completionist
(15)
π§
Keyword Pioneer
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Keyword Trendsetter Combo
(4)
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Conference Loyalist
(23)
π€
Dynamic Duo
(23)
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Century Club
(24)
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Unstoppable
(7)
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Trend Setter
ποΈ
Keyword Collector
(150)
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Prolific Year
(8)
Conferences
NIPS (23)
IJCAI (1)
Top co-authors
Keywords
reinforcement learning
(3)
variational inference
(3)
stochastic optimization
(3)
image classification
(3)
gaussian process
(3)
distributed learning
(2)
distributed machine learning
(2)
latent variable model
(2)
convolutional neural network
(2)
semi-supervised learning
(2)
stochastic gradient
(2)
stochastic gradient descent
(2)
bayesian inference
(2)
bayesian nonparametrics
(2)
variance reduction
(2)
generative adversarial network
(2)
adversarial robustness
(1)
feature learning
(1)
multi-task learning
(1)
probabilistic modeling
(1)
Papers
Learning Robust Global Representations by Penalizing Local Predictive Power
NIPS 2019
Learning Data Manipulation for Augmentation and Weighting
NIPS 2019
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering
NIPS 2019
Learning Sample-Specific Models with Low-Rank Personalized Regression
NIPS 2019
Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation
NIPS 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning
NIPS 2018
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
NIPS 2018
The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models
NIPS 2018
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems
NIPS 2018
Symbolic Graph Reasoning Meets Convolutions
NIPS 2018
Deep Generative Models with Learnable Knowledge Constraints
NIPS 2018
Unsupervised Text Style Transfer using Language Models as Discriminators
NIPS 2018
Structured Generative Adversarial Networks
NIPS 2017
Variance Reduction in Stochastic Gradient Langevin Dynamics
NIPS 2016
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices
NIPS 2016
Stochastic Variational Deep Kernel Learning
NIPS 2016
Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection
IJCAI 2015
The Human Kernel
NIPS 2015
On Model Parallelization and Scheduling Strategies for Distributed Machine Learning
NIPS 2014
Dependent nonparametric trees for dynamic hierarchical clustering
NIPS 2014
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server
NIPS 2013
Variance Reduction for Stochastic Gradient Optimization
NIPS 2013
Restricting exchangeable nonparametric distributions
NIPS 2013
A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks
NIPS 2013