← Authors

Eric P Xing

24 papers · 2013–2019 · 2 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (2) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (6) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14) πŸ—ΊοΈ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (4) 🏠 Conference Loyalist (23) 🀝 Dynamic Duo (23) πŸ’Ž Century Club (24) πŸ”₯ Unstoppable (7) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (150) ⚑ Prolific Year (8)

Conferences

NIPS (23) IJCAI (1)

Top co-authors

Eric P. Xing (23) Zhiting Hu (6) Qirong Ho (4) Xiaodan Liang (4) Bryon Aragam (3) Ruslan Salakhutdinov (3) Sinead A Williamson (3) Kumar Avinava Dubey (3) Tom M. Mitchell (2) Hao Zhang (2)

Keywords

reinforcement learning (3) variational inference (3) stochastic optimization (3) image classification (3) gaussian process (3) distributed learning (2) generative adversarial network (2) latent variable model (2) bayesian nonparametric (2) semi-supervised learning (2) stochastic gradient (2) stochastic gradient descent (2) bayesian inference (2) distributed machine learning (2) variance reduction (2) convolutional neural network (2) image generation (1) adversarial robustness (1) feature learning (1) multi-task learning (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