Eric P Xing
24 papers · 2013–2019 · 2 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+10 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (71) π Conference Polyglot Β· Bronze π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Conference Loyalist
(23)
π€
Dynamic Duo
(23)
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(5)
π
Renaissance Researcher
(9)
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
π
Century Club Β· Bronze
π
Trend Setter
ποΈ
Keyword Collector
(158)
Venues
Top co-authors
Research topics
Machine Learning
(21)
Core Methods
(12)
Artificial Intelligence
(11)
Optimization & Theory
(11)
Learning Types Β· Machine Learning
(10)
Deep Learning
(9)
Bayesian & Probabilistic Β· Machine Learning
(9)
Mathematics & Optimization
(5)
Bayesian & Probabilistic Β· Artificial Intelligence
(5)
Core AI
(5)
Application Areas
(4)
Learning Paradigms
(4)
Learning Types Β· Deep Learning
(4)
Models
(4)
Optimization
(4)
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 Data Manipulation for Augmentation and Weighting
NeurIPS 2019
Learning Robust Global Representations by Penalizing Local Predictive Power
NeurIPS 2019
Learning Sample-Specific Models with Low-Rank Personalized Regression
NeurIPS 2019
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering
NeurIPS 2019
DAGs with NO TEARS: Continuous Optimization for Structure Learning
NeurIPS 2018
Deep Generative Models with Learnable Knowledge Constraints
NeurIPS 2018
Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation
NeurIPS 2018
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems
NeurIPS 2018
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
NeurIPS 2018
Symbolic Graph Reasoning Meets Convolutions
NeurIPS 2018
The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models
NeurIPS 2018
Unsupervised Text Style Transfer using Language Models as Discriminators
NeurIPS 2018
Structured Generative Adversarial Networks
NeurIPS 2017
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices
NeurIPS 2016
Stochastic Variational Deep Kernel Learning
NeurIPS 2016
Variance Reduction in Stochastic Gradient Langevin Dynamics
NeurIPS 2016
Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection
IJCAI 2015
The Human Kernel
NeurIPS 2015
Dependent nonparametric trees for dynamic hierarchical clustering
NeurIPS 2014
On Model Parallelization and Scheduling Strategies for Distributed Machine Learning
NeurIPS 2014
A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks
NeurIPS 2013
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server
NeurIPS 2013
Restricting exchangeable nonparametric distributions
NeurIPS 2013
Variance Reduction for Stochastic Gradient Optimization
NeurIPS 2013