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Qiang Liu
Qiang Liu
Associate Professor of Computer Science, UT Austin
Verified email at cs.utexas.edu - Homepage
Title
Cited by
Cited by
Year
Stein variational gradient descent: A general purpose Bayesian inference algorithm
Q Liu, D Wang
Advances In Neural Information Processing Systems, 2370-2378, 2016
11872016
A kernelized Stein discrepancy for goodness-of-fit tests
Q Liu, J Lee, M Jordan
International conference on machine learning, 276-284, 2016
5312016
Variational inference for crowdsourcing
Q Liu, J Peng, AT Ihler
Advances in Neural Information Processing Systems, 692-700, 2012
4162012
Breaking the curse of horizon: Infinite-horizon off-policy estimation
Q Liu, L Li, Z Tang, D Zhou
arXiv preprint arXiv:1810.12429, 2018
3882018
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
X Liu, C Gong, Q Liu
arXiv preprint arXiv:2209.03003, 2022
3312022
Stein variational gradient descent as gradient flow
Q Liu
Advances in neural information processing systems, 3115-3123, 2017
3052017
Brain and muscle Arnt-like protein-1 (BMAL1) controls circadian cell proliferation and susceptibility to UVB-induced DNA damage in the epidermis
M Geyfman, V Kumar, Q Liu, R Ruiz, W Gordon, F Espitia, E Cam, ...
Proceedings of the National Academy of Sciences 109 (29), 11758-11763, 2012
2772012
Conflict-Averse Gradient Descent for Multi-task Learning
B Liu, X Liu, X Jin, P Stone, Q Liu
arXiv preprint arXiv:2110.14048, 2021
2612021
Llm+ p: Empowering large language models with optimal planning proficiency
B Liu, Y Jiang, X Zhang, Q Liu, S Zhang, J Biswas, P Stone
arXiv preprint arXiv:2304.11477, 2023
2582023
Communication-efficient Sparse Regression
JD Lee, Q Liu, Y Sun, JE Taylor
Journal of Machine Learning Research 18 (5), 1-30, 2017
2352017
Regularization matters: Generalization and optimization of neural nets vs their induced kernel
C Wei, JD Lee, Q Liu, T Ma
Advances in Neural Information Processing Systems, 9709-9721, 2019
2162019
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning
D Wang, Q Liu
arXiv preprint arXiv:1611.01722, 2016
2032016
Stein Variational Policy Gradient
Y Liu, P Ramachandran, Q Liu, J Peng
arXiv preprint arXiv:1704.02399, 2017
1582017
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
C Gong, D Wang, M Li, V Chandra, Q Liu
arXiv preprint arXiv:2011.11778, 2020
1422020
Practical human sensing in the light
T Li, Q Liu, X Zhou
Proceedings of the 14th Annual International Conference on Mobile Systems …, 2016
1422016
On the Discrimination-Generalization Tradeoff in GANs
P Zhang, Q Liu, D Zhou, T Xu, X He
arXiv preprint arXiv:1711.02771, 2017
1362017
Aggregating ordinal labels from crowds by minimax conditional entropy
D Zhou, Q Liu, J Platt, C Meek
International conference on machine learning, 262-270, 2014
1312014
An optimization view on dynamic routing between capsules
D Wang, Q Liu
1272018
Improving Neural Language Modeling via Adversarial Training
D Wang, C Gong, Q Liu
arXiv preprint arXiv:1906.03805, 2019
1172019
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
M Ye, C Gong, L Nie, D Zhou, A Klivans, Q Liu
arXiv preprint arXiv:2003.01794, 2020
1142020
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