Sotabase

Career

· Associate Professor, The University of Hong Kong2024–
· Associate Professor, University of Wisconsin-Madison2017–
· Associate Researcher, Princeton University2016–
· Postdoctoral Researcher / Associate Research Scholar, Princeton University2014–2017
· PhD in Computer Science, Georgia Institute of Technology2010–2014
· Postdoctoral Researcher, Princeton University2010–2014
· MS in Computer Science, Tsinghua University2008–2010
· B.S. in Computer Science, Tsinghua University2004–2008
· Assistant Professor, University of California, San Diego
· Adjunct Professor, University of Wisconsin-Madison
· Assistant Professor, University of Wisconsin-Madison

Publications (114)

A Simple but Tough-to-Beat Baseline for Sentence Embeddings
International Conference on Learning Representations · 2017
1,382
cited
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
Neural Information Processing Systems · 2018
817
cited
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
International Conference on Machine Learning · 2017
712
cited
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
Neural Information Processing Systems · 2018
672
cited
Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis
AAAI Conference on Artificial Intelligence · 2019
394
cited
A Latent Variable Model Approach to PMI-based Word Embeddings
Transactions of the Association for Computational Linguistics · 2015
380
cited
Linear Algebraic Structure of Word Senses, with Applications to Polysemy
Transactions of the Association for Computational Linguistics · 2016
316
cited
Scalable Kernel Methods via Doubly Stochastic Gradients
Neural Information Processing Systems · 2014
233
cited
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules
Neural Information Processing Systems · 2018
221
cited
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning
AAAI Conference on Artificial Intelligence · 2019
173
cited
ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining
ECML/PKDD · 2020
168
cited
Improved Distributed Principal Component Analysis
Neural Information Processing Systems · 2014
156
cited
Diverse Neural Network Learns True Target Functions
International Conference on Artificial Intelligence and Statistics · 2016
146
cited
Distributed k-Means and k-Median Clustering on General Topologies
Neural Information Processing Systems · 2013
129
cited
Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials
npj Computational Materials · 2020
121
cited
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
Annual Meeting of the Association for Computational Linguistics · 2018
106
cited
Robust Out-of-distribution Detection for Neural Networks
2020
98
cited
Can Adversarial Weight Perturbations Inject Neural Backdoors
International Conference on Information and Knowledge Management · 2020
96
cited
Clustering under Perturbation Resilience
SIAM journal on computing (Print) · 2011
93
cited
Robust Attribution Regularization
Neural Information Processing Systems · 2019
88
cited
Sotabase