Ruqi Zhang

According to our database, Ruqi Zhang authored at least 26 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World.

Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick

CoRR, 2024

Gradient-based Discrete Sampling with Automatic Cyclical Scheduling.

Patrick Pynadath, Riddhiman Bhattacharya, Arun Hariharan, Ruqi Zhang

CoRR, 2024

Training Bayesian Neural Networks with Sparse Subspace Variational Inference.

Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang

CoRR, 2024

Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI.

Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang

CoRR, 2024

2023

Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo.

Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang

CoRR, 2023

Entropy-MCMC: Sampling from Flat Basins with Ease.

Bolian Li, Ruqi Zhang

CoRR, 2023

Long-tailed Classification from a Bayesian-decision-theory Perspective.

Bolian Li, Ruqi Zhang

CoRR, 2023

Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction.

Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani K. Mallick

CoRR, 2023

DISCS: A Benchmark for Discrete Sampling.

Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference.

Wanrong Zhang, Ruqi Zhang

Proceedings of the International Conference on Machine Learning, 2023

Calibrating the Rigged Lottery: Making All Tickets Reliable.

Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Rethinking Data Distillation: Do Not Overlook Calibration.

Dongyao Zhu, Yanbo Fang, Bowen Lei, Yiqun Xie, Dongkuan Xu, Jie Zhang, Ruqi Zhang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation.

Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging.

Tunazzina Islam, Ruqi Zhang, Dan Goldwasser

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent.

Ruqi Zhang, Qiang Liu, Xin T. Tong

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Low-Precision Stochastic Gradient Langevin Dynamics.

Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa

Proceedings of the International Conference on Machine Learning, 2022

A Langevin-like Sampler for Discrete Distributions.

Ruqi Zhang, Xingchao Liu, Qiang Liu

Proceedings of the International Conference on Machine Learning, 2022

2021

Meta-Learning Divergences for Variational Inference.

Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Meta-Learning for Variational Inference.

Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang

CoRR, 2020

Asymptotically Optimal Exact Minibatch Metropolis-Hastings.

Ruqi Zhang, A. Feder Cooper, Christopher De Sa

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning.

Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson

Proceedings of the 8th International Conference on Learning Representations, 2020

AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC.

Ruqi Zhang, A. Feder Cooper, Christopher De Sa

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees.

Ruqi Zhang, Christopher De Sa

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Acupoint Selection Rule Mining of Premature Ovarian Failure Treatment with Acupuncture and Moxibustion Based on the Data Analysis of Clinical Literature.

Xiaochun Han, Yanni Fan, Haijun Zhao, Shijun Wang, Sisheng Tian, Hongyuan Zhang, Zhe Yang, Ruqi Zhang, Jing Zhang, Wei Shi

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2016

Large Scale Sparse Clustering.

Ruqi Zhang, Zhiwu Lu

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Denoising Cluster Analysis.

Ruqi Zhang, Zhirong Yang, Jukka Corander

Proceedings of the Neural Information Processing - 22nd International Conference, 2015