default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDQiang Liu 0001
Person information
- affiliation: University of Texas at Austin, Department of Computer Science, TX, USA
- affiliation (former): Dartmouth College, Department of Computer Science, Hanover, NH, USA
- affiliation (former): University of California, Irvine, Department of Computer Science, CA, USA
Other persons with the same name
- Qiang Liu — disambiguation page
- Qiang Liu 0002 — Linköping University, Swedish e-Science Research Centre, Sweden
- Qiang Liu 0003
![[0000-0001-7531-4459]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-7531-4459")
— University of Essex, School of Computer Science and Electronic Engineering, Colchester, UK - Qiang Liu 0004 — National University of Defense Technology, College of Computer, Changsha, China
- Qiang Liu 0005 — Delft University of Technology, The Netherlands (and 1 more)
- Qiang Liu 0006 — Chinese Academy of Sciences, Institute of Automation, Center for Research on Intelligent Perception and Computing, Beijing, China
- Qiang Liu 0007 — Oak Ridge National Laboratory, Computer Science and Mathematics Division, TN, USA (and 1 more)
- Qiang Liu 0008 — Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China (and 1 more)
- Qiang Liu 0009 — Joint Center for Global Change Studies, Beijing, China (and 2 more)
- Qiang Liu 0010 — Liaoning Shihua University, School of Information and Control Engineering, Fushun, China (and 1 more)
- Qiang Liu 0011 — Tianjin University, School of Microelectronics, China (and 1 more)
- Qiang Liu 0012 — Huaihai Institute of Technology, School of Electric Engineering, Lianyungang, China
- Qiang Liu 0013 — University of Nebraska-Lincoln, NE, USA (and 1 more)
- Qiang Liu 0014 — Beijing Jiaotong University, School of Computer and Information Technology, China
- Qiang Liu 0015 — Chinese University of Hong Kong
- Qiang Liu 0016 — University of Electronic Science and Technology of China, School of Communication and Information Engineering, Chengdu, China
- Qiang Liu 0017 — Hunan University, College of Electrical and Information Engineering, Changsha, China (and 1 more)
- Qiang Liu 0018 — Northeastern University, State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, China
- Qiang Liu 0019 — University of Manchester, School of Engineering, UK
- Qiang Liu 0020 — Beijing Jiaotong University, Beijing Key Laboratory of Transportation Data Analysis and Mining, China
- Qiang Liu 0021 — Sichuan University, College of Electronics and Information Engineering, Chengdu, China
- Qiang Liu 0022 — University of Antwerp, Department of Biology, Belgium (and 1 more)
- Qiang Liu 0023 — Dalian University of Technology, School of Mechanical Engineering, China
- Qiang Liu 0024 — Beihang University, School of Mechanical Engineering and Automation, Beijing, China
- Qiang Liu 0025 — Shenzhen University, School of Mathematics and Statistics, China (and 1 more)
- Qiang Liu 0026 — Shandong University of Finance and Economics, Department of Network and Information Security, Jinan, China (and 1 more)
- Qiang Liu 0027 — Chinese Academy of Sciences, Changchun Institute of Optics, Fine Mechanics and Physics, China
- Qiang Liu 0028 — Harbin Institute of Technology, State Key Laboratory of Robotics and System, China
- Qiang Liu 0029 — Beijing Institute of Petrochemical Technology, Institute of Precision Electromagnetic Equipment and Advanced Measurement Technology, China (and 1 more)
- Qiang Liu 0030 — Beijing University of Posts and Telecommunications, School of Information and Communication, China
- Qiang Liu 0031 — Guangdong University of Technology, Guangzhou, China
- Qiang Liu 0032 — Hunan University of Technology, College of Computer Science, Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory, Zhuzhou, China
- Qiang Liu 0033 — University of Pittsburgh, Department of Neurological Surgery, PA, USA
- Qiang Liu 0034 — EPFL, Lausanne, Vaud, Switzerland (and 1 more)
- Qiang Liu 0035 — Ningbo University, Faculty of Electrical Engineering and Computer Science, China
- Qiang Liu 0036 — Alibaba Group, China
- Qiang Liu 0037 — Beijing Normal University, College of Global Change and Earth System Science, Beijing, China
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[c113]Lemeng Wu, Dilin Wang, Meng Li, Yunyang Xiong, Raghuraman Krishnamoorthi, Qiang Liu, Vikas Chandra:
PathFusion: Path-Consistent Lidar-Camera Deep Feature Fusion. 3DV 2024: 313-323- [c112]Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu, Dhruv Choudhary, Arun Kejariwal, Qiang Liu:
Layer Compression of Deep Networks with Straight Flows. AAAI 2024: 12181-12189 - [c111]Peihao Wang, Dejia Xu, Zhiwen Fan, Dilin Wang, Sreyas Mohan, Forrest N. Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra:
Taming Mode Collapse in Score Distillation for Text-to-3D Generation. CVPR 2024: 9037-9047 - [c110]Lizhang Chen, Bo Liu, Kaizhao Liang, Qiang Liu:
Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts. ICLR 2024 - [c109]Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu:
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation. ICLR 2024 - [c108]Chengyue Gong, Adam R. Klivans, James Loy, Tianlong Chen, Qiang Liu, Daniel Jesus Diaz:
Evolution-Inspired Loss Functions for Protein Representation Learning. ICML 2024 - [c107]Ruidong Wu, Ruihan Guo, Rui Wang, Shitong Luo, Yue Xu, Jiahan Li, Jianzhu Ma, Qiang Liu, Yunan Luo, Jian Peng:
FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames. ICML 2024 - [i107]Peihao Wang, Zhiwen Fan, Dejia Xu, Dilin Wang, Sreyas Mohan, Forrest N. Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra:
SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity. CoRR abs/2401.00604 (2024) - [i106]Peihao Wang, Dejia Xu, Zhiwen Fan, Dilin Wang, Sreyas Mohan, Forrest N. Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra:
Taming Mode Collapse in Score Distillation for Text-to-3D Generation. CoRR abs/2401.00909 (2024) - [i105]Xixi Hu, Bo Liu, Xingchao Liu, Qiang Liu:
AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies. CoRR abs/2402.04292 (2024) - [i104]Bo Liu, Lemeng Wu, Lizhang Chen, Kaizhao Liang, Jiaxu Zhu, Chen Liang, Raghuraman Krishnamoorthi, Qiang Liu:
Communication Efficient Distributed Training with Distributed Lion. CoRR abs/2404.00438 (2024) - [i103]Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, Jiashi Feng:
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator. CoRR abs/2405.07510 (2024) - [i102]Son Nguyen, Lizhang Chen, Bo Liu, Qiang Liu:
H-Fac: Memory-Efficient Optimization with Factorized Hamiltonian Descent. CoRR abs/2406.09958 (2024) - [i101]Ruidong Wu, Ruihan Guo, Rui Wang, Shitong Luo, Yue Xu, Jiahan Li, Jianzhu Ma, Qiang Liu, Yunan Luo, Jian Peng:
FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames. CoRR abs/2407.01649 (2024) - [i100]Yuanzhi Zhu, Xingchao Liu, Qiang Liu:
SlimFlow: Training Smaller One-Step Diffusion Models with Rectified Flow. CoRR abs/2407.12718 (2024) - [i99]Bo Liu, Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, Qiang Liu:
Longhorn: State Space Models are Amortized Online Learners. CoRR abs/2407.14207 (2024) - [i98]Kaizhao Liang, Bo Liu, Lizhang Chen, Qiang Liu:
Memory-Efficient LLM Training with Online Subspace Descent. CoRR abs/2408.12857 (2024) - [i97]Kevin Wang, Junbo Li, Neel P. Bhatt, Yihan Xi, Qiang Liu, Ufuk Topcu, Zhangyang Wang:
On The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability. CoRR abs/2409.19924 (2024) - [i96]Bo Liu, Mao Ye, Peter Stone, Qiang Liu:
Fine-Grained Gradient Restriction: A Simple Approach for Mitigating Catastrophic Forgetting. CoRR abs/2410.00868 (2024) - [i95]Daiheng Zhang, Chengyue Gong, Qiang Liu:
Rectified Flow For Structure Based Drug Design. CoRR abs/2412.01174 (2024) - 2023
- [c106]Bo Liu, Yihao Feng, Qiang Liu, Peter Stone:
Metric Residual Network for Sample Efficient Goal-Conditioned Reinforcement Learning. AAAI 2023: 8799-8806 - [c105]Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu:
Fast Point Cloud Generation with Straight Flows. CVPR 2023: 9445-9454 - [c104]Xingchao Liu, Lemeng Wu, Shujian Zhang, Chengyue Gong, Wei Ping, Qiang Liu:
FlowGrad: Controlling the Output of Generative ODEs with Gradients. CVPR 2023: 24335-24344 - [c103]Mao Ye, Gregory P. Meyer, Yuning Chai, Qiang Liu:
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting. ICCV 2023: 8404-8416 - [c102]Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew D. Ellington, Alex Dimakis, Adam R. Klivans:
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing. ICLR 2023 - [c101]Xingchao Liu, Chengyue Gong, Qiang Liu:
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. ICLR 2023 - [c100]Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu:
Learning Diffusion Bridges on Constrained Domains. ICLR 2023 - [c99]Xingang Peng, Jiaqi Guan, Qiang Liu, Jianzhu Ma:
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation. ICML 2023: 27611-27629 - [c98]Bo Liu, Yihao Feng, Peter Stone, Qiang Liu:
FAMO: Fast Adaptive Multitask Optimization. NeurIPS 2023 - [c97]Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone:
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning. NeurIPS 2023 - [i94]Mao Ye, Gregory P. Meyer, Yuning Chai, Qiang Liu:
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting. CoRR abs/2303.05078 (2023) - [i93]Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, Peter Stone:
LLM+P: Empowering Large Language Models with Optimal Planning Proficiency. CoRR abs/2304.11477 (2023) - [i92]Xingang Peng, Jiaqi Guan, Qiang Liu, Jianzhu Ma:
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation. CoRR abs/2305.07508 (2023) - [i91]Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu, Yuke Zhu, Peter Stone:
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning. CoRR abs/2306.03310 (2023) - [i90]Bo Liu, Yihao Feng, Peter Stone, Qiang Liu:
FAMO: Fast Adaptive Multitask Optimization. CoRR abs/2306.03792 (2023) - [i89]Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu:
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation. CoRR abs/2309.06380 (2023) - [i88]Lizhang Chen, Bo Liu, Kaizhao Liang, Qiang Liu:
Lion Secretly Solves Constrained Optimization: As Lyapunov Predicts. CoRR abs/2310.05898 (2023) - 2022
- [j12]Di Wu, Zhanxiu Zeng, Fengrui Shi, Weiren Yu, Tao Wu, Qiang Liu:
Human as a Service: Towards Resilient Parking Search System With Sensorless Sensing. IEEE Trans. Intell. Transp. Syst. 23(8): 13863-13877 (2022) - [c96]Bo Liu, Qiang Liu, Peter Stone:
Continual Learning and Private Unlearning. CoLLAs 2022: 243-254 - [c95]Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra:
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. ICLR 2022 - [c94]Jiaqi Guan, Wesley Wei Qian, Qiang Liu, Wei-Ying Ma, Jianzhu Ma, Jian Peng:
Energy-Inspired Molecular Conformation Optimization. ICLR 2022 - [c93]Chengyue Gong, Lemeng Wu, Qiang Liu:
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity. ICML 2022: 7650-7664 - [c92]Mao Ye, Qiang Liu:
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference. ICML 2022: 25469-25489 - [c91]Ruqi Zhang, Xingchao Liu, Qiang Liu:
A Langevin-like Sampler for Discrete Distributions. ICML 2022: 26375-26396 - [c90]Chengyue Gong, Xiaocong Du, Dhruv Choudhary, Bhargav Bhushanam, Qiang Liu, Arun Kejariwal:
Harmless Transfer Learning for Item Embeddings. NAACL-HLT (Findings) 2022: 504-516 - [c89]Bo Liu, Mao Ye, Stephen Wright, Peter Stone, Qiang Liu:
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach. NeurIPS 2022 - [c88]Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu:
Diffusion-based Molecule Generation with Informative Prior Bridges. NeurIPS 2022 - [c87]Mao Ye, Lemeng Wu, Qiang Liu:
First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data. NeurIPS 2022 - [c86]Ruqi Zhang, Qiang Liu, Xin T. Tong:
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent. NeurIPS 2022 - [c85]Mao Ye, Qiang Liu:
Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set. UAI 2022: 2246-2255 - [c84]Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu:
Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. UAI 2022: 2256-2266 - [i87]Ziyang Tang, Yihao Feng, Qiang Liu:
Operator Deep Q-Learning: Zero-Shot Reward Transferring in Reinforcement Learning. CoRR abs/2201.00236 (2022) - [i86]Chengyue Gong, Lemeng Wu, Qiang Liu:
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity. CoRR abs/2202.08376 (2022) - [i85]Bo Liu, Qiang Liu, Peter Stone:
Continual Learning and Private Unlearning. CoRR abs/2203.12817 (2022) - [i84]Ruqi Zhang, Xingchao Liu, Qiang Liu:
A Langevin-like Sampler for Discrete Distributions. CoRR abs/2206.09914 (2022) - [i83]Xing Han, Ziyang Tang, Joydeep Ghosh, Qiang Liu:
Split Localized Conformal Prediction. CoRR abs/2206.13092 (2022) - [i82]Bo Liu, Yihao Feng, Qiang Liu, Peter Stone:
Metric Residual Networks for Sample Efficient Goal-conditioned Reinforcement Learning. CoRR abs/2208.08133 (2022) - [i81]Xingchao Liu, Lemeng Wu, Mao Ye, Qiang Liu:
Let us Build Bridges: Understanding and Extending Diffusion Generative Models. CoRR abs/2208.14699 (2022) - [i80]Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu:
Diffusion-based Molecule Generation with Informative Prior Bridges. CoRR abs/2209.00865 (2022) - [i79]Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu:
Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems. CoRR abs/2209.01143 (2022) - [i78]Mao Ye, Lemeng Wu, Qiang Liu:
First Hitting Diffusion Models. CoRR abs/2209.01170 (2022) - [i77]Xingchao Liu, Chengyue Gong, Qiang Liu:
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. CoRR abs/2209.03003 (2022) - [i76]Mao Ye, Bo Liu, Stephen Wright, Peter Stone, Qiang Liu:
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach. CoRR abs/2209.08709 (2022) - [i75]Yan Zheng, Lemeng Wu, Xingchao Liu, Zhen Chen, Qiang Liu, Qixing Huang:
Neural Volumetric Mesh Generator. CoRR abs/2210.03158 (2022) - [i74]Ruqi Zhang, Qiang Liu, Xin T. Tong:
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent. CoRR abs/2210.06447 (2022) - [i73]Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu:
Fast Point Cloud Generation with Straight Flows. CoRR abs/2212.01747 (2022) - [i72]Lemeng Wu, Dilin Wang, Meng Li, Yunyang Xiong, Raghuraman Krishnamoorthi, Qiang Liu, Vikas Chandra:
PathFusion: Path-consistent Lidar-Camera Deep Feature Fusion. CoRR abs/2212.06244 (2022) - 2021
- [j11]Xiao Bai, Xiang Wang, Xianglong Liu, Qiang Liu, Jingkuan Song, Nicu Sebe, Been Kim:
Explainable deep learning for efficient and robust pattern recognition: A survey of recent developments. Pattern Recognit. 120: 108102 (2021) - [j10]Aishan Liu, Xianglong Liu, Hang Yu, Chongzhi Zhang, Qiang Liu, Dacheng Tao:
Training Robust Deep Neural Networks via Adversarial Noise Propagation. IEEE Trans. Image Process. 30: 5769-5781 (2021) - [c83]Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu:
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. AAAI 2021: 8697-8705 - [c82]Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu:
KeepAugment: A Simple Information-Preserving Data Augmentation Approach. CVPR 2021: 1055-1064 - [c81]Chengyue Gong, Tongzheng Ren, Mao Ye, Qiang Liu:
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. CVPR 2021: 2474-2483 - [c80]Chengyue Gong, Dilin Wang, Qiang Liu:
AlphaMatch: Improving Consistency for Semi-Supervised Learning With Alpha-Divergence. CVPR 2021: 13683-13692 - [c79]Yihao Feng, Ziyang Tang, Na Zhang, Qiang Liu:
Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds. ICLR 2021 - [c78]Lizhen Nie, Mao Ye, Qiang Liu, Dan Nicolae:
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments. ICLR 2021 - [c77]Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar:
Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition. ICML 2021: 6860-6870 - [c76]Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra:
AlphaNet: Improved Training of Supernets with Alpha-Divergence. ICML 2021: 10760-10771 - [c75]Chengyue Gong, Mao Ye, Qiang Liu:
argmax centroid. NeurIPS 2021: 7012-7024 - [c74]Xingchao Liu, Xin Tong, Qiang Liu:
Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent. NeurIPS 2021: 14721-14733 - [c73]Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu:
Conflict-Averse Gradient Descent for Multi-task learning. NeurIPS 2021: 18878-18890 - [c72]Xingchao Liu, Xin Tong, Qiang Liu:
Sampling with Trusthworthy Constraints: A Variational Gradient Framework. NeurIPS 2021: 23557-23568 - [c71]Chengyue Gong, Xingchao Liu, Qiang Liu:
Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach. NeurIPS 2021: 29630-29642 - [i71]Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra:
AlphaNet: Improved Training of Supernet with Alpha-Divergence. CoRR abs/2102.07954 (2021) - [i70]Lemeng Wu, Bo Liu, Peter Stone, Qiang Liu:
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks. CoRR abs/2102.08574 (2021) - [i69]Lemeng Wu, Xingchao Liu, Qiang Liu:
Centroid Transformers: Learning to Abstract with Attention. CoRR abs/2102.08606 (2021) - [i68]Yihao Feng, Ziyang Tang, Na Zhang, Qiang Liu:
Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds. CoRR abs/2103.05741 (2021) - [i67]Lizhen Nie, Mao Ye, Qiang Liu, Dan Nicolae:
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments. CoRR abs/2103.07861 (2021) - [i66]Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu:
Improve Vision Transformers Training by Suppressing Over-smoothing. CoRR abs/2104.12753 (2021) - [i65]Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Animashree Anandkumar:
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition. CoRR abs/2105.08692 (2021) - [i64]Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou:
Speeding up Deep Model Training by Sharing Weights and Then Unsharing. CoRR abs/2110.03848 (2021) - [i63]Mao Ye, Qiang Liu:
Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto Set. CoRR abs/2110.08713 (2021) - [i62]Mao Ye, Qiang Liu:
Centroid Approximation for Bootstrap. CoRR abs/2110.08720 (2021) - [i61]Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu:
Conflict-Averse Gradient Descent for Multi-task Learning. CoRR abs/2110.14048 (2021) - [i60]Xingchao Liu, Chengyue Gong, Lemeng Wu, Shujian Zhang, Hao Su, Qiang Liu:
FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization. CoRR abs/2112.01573 (2021) - 2020
- [j9]Qiang Liu, Xin T. Tong:
Accelerating Metropolis-within-Gibbs sampler with localized computations of differential equations. Stat. Comput. 30(4): 1037-1056 (2020) - [j8]Di Wu, Lambros Lambrinos, Thomas Przepiorka, Dmitri I. Arkhipov, Qiang Liu, Amelia C. Regan, Julie A. McCann:
Enabling Efficient Offline Mobile Access to Online Social Media on Urban Underground Metro Systems. IEEE Trans. Intell. Transp. Syst. 21(7): 2750-2764 (2020) - [c70]Mao Ye, Chengyue Gong, Qiang Liu:
SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions. ACL 2020: 3465-3475 - [c69]Jun Han, Fan Ding, Xianglong Liu, Lorenzo Torresani, Jian Peng, Qiang Liu:
Stein Variational Inference for Discrete Distributions. AISTATS 2020: 4563-4572 - [c68]Ali Mousavi, Lihong Li, Qiang Liu, Denny Zhou:
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning. ICLR 2020 - [c67]Ziyang Tang, Yihao Feng, Lihong Li, Dengyong Zhou, Qiang Liu:
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation. ICLR 2020 - [c66]Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu:
Accountable Off-Policy Evaluation With Kernel Bellman Statistics. ICML 2020: 3102-3111 - [c65]Xianggen Liu, Qiang Liu, Sen Song, Jian Peng:
A Chance-Constrained Generative Framework for Sequence Optimization. ICML 2020: 6271-6281 - [c64]Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam R. Klivans, Qiang Liu:
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection. ICML 2020: 10820-10830 - [c63]Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans:
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. ICML 2020: 11546-11555 - [c62]Xingchao Liu, Xing Han, Na Zhang, Qiang Liu:
Certified Monotonic Neural Networks. NeurIPS 2020 - [c61]Ziyang Tang, Yihao Feng, Na Zhang, Jian Peng, Qiang Liu:
Off-Policy Interval Estimation with Lipschitz Value Iteration. NeurIPS 2020 - [c60]Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel A. Ward, Qiang Liu:
Implicit Regularization and Convergence for Weight Normalization. NeurIPS 2020 - [c59]Lemeng Wu, Bo Liu, Peter Stone, Qiang Liu:
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks. NeurIPS 2020 - [c58]Mao Ye, Tongzheng Ren, Qiang Liu:
Stein Self-Repulsive Dynamics: Benefits From Past Samples. NeurIPS 2020 - [c57]Mao Ye, Lemeng Wu, Qiang Liu:
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough. NeurIPS 2020 - [c56]Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu:
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. NeurIPS 2020 - [i59]ChengYue Gong, Tongzheng Ren, Mao Ye, Qiang Liu:
MaxUp: A Simple Way to Improve Generalization of Neural Network Training. CoRR abs/2002.09024 (2020) - [i58]Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu:
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. CoRR abs/2002.09049 (2020) - [i57]Mao Ye, Tongzheng Ren, Qiang Liu:
Stein Self-Repulsive Dynamics: Benefits From Past Samples. CoRR abs/2002.09070 (2020) - [i56]Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu:
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. CoRR abs/2002.09169 (2020) - [i55]