Ruqi Zhang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 43

Top Topics

Variational Inference

Metropolis Hastings

Top Venues

Publications

Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick
Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World. CoRR (2024)
Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang
Training Bayesian Neural Networks with Sparse Subspace Variational Inference. CoRR (2024)
Patrick Pynadath, Riddhiman Bhattacharya, Arun Hariharan, Ruqi Zhang
Gradient-based Discrete Sampling with Automatic Cyclical Scheduling. CoRR (2024)
Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. Trans. Mach. Learn. Res. 2024 (2024)
Bolian Li, Ruqi Zhang
Entropy-MCMC: Sampling from Flat Basins with Ease. ICLR (2024)
Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang
Training Bayesian Neural Networks with Sparse Subspace Variational Inference. ICLR (2024)
Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani K. Mallick
Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World. Trans. Mach. Learn. Res. 2024 (2024)
Xukun Liu, Bowen Lei, Ruqi Zhang, Dongkuan Xu
Adaptive Draft-Verification for Efficient Large Language Model Decoding. CoRR (2024)
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
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR (2024)
Bolian Li, Yifan Wang, Ananth Grama, Ruqi Zhang
Cascade Reward Sampling for Efficient Decoding-Time Alignment. CoRR (2024)
Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation. CoRR (2023)
Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick
Calibrating the Rigged Lottery: Making All Tickets Reliable. ICLR (2023)
Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani K. Mallick
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction. CoRR (2023)
Bolian Li, Ruqi Zhang
Long-tailed Classification from a Bayesian-decision-theory Perspective. CoRR (2023)
Dongyao Zhu, Yanbo Fang, Bowen Lei, Yiqun Xie, Dongkuan Xu, Jie Zhang, Ruqi Zhang
Rethinking Data Distillation: Do Not Overlook Calibration. ICCV (2023)
Bolian Li, Ruqi Zhang
Entropy-MCMC: Sampling from Flat Basins with Ease. CoRR (2023)
Wanrong Zhang, Ruqi Zhang
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference. CoRR (2023)
Bowen Lei, Ruqi Zhang, Dongkuan Xu, Bani K. Mallick
Calibrating the Rigged Lottery: Making All Tickets Reliable. CoRR (2023)
Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation. AISTATS (2023)
Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo. CoRR (2023)
Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai
DISCS: A Benchmark for Discrete Sampling. NeurIPS (2023)
Tunazzina Islam, Ruqi Zhang, Dan Goldwasser
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging. CoRR (2023)
Dongyao Zhu, Bowen Lei, Jie Zhang, Yanbo Fang, Ruqi Zhang, Yiqun Xie, Dongkuan Xu
Rethinking Data Distillation: Do Not Overlook Calibration. CoRR (2023)
Tunazzina Islam, Ruqi Zhang, Dan Goldwasser
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging. AIES (2023)
Wanrong Zhang, Ruqi Zhang
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference. ICML (2023)
Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa
Low-Precision Stochastic Gradient Langevin Dynamics. ICML (2022)
Ruqi Zhang, Qiang Liu, Xin T. Tong
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent. CoRR (2022)
Ruqi Zhang, Xingchao Liu, Qiang Liu
A Langevin-like Sampler for Discrete Distributions. CoRR (2022)
Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa
Low-Precision Stochastic Gradient Langevin Dynamics. CoRR (2022)
Ruqi Zhang, Xingchao Liu, Qiang Liu
A Langevin-like Sampler for Discrete Distributions. ICML (2022)
Ruqi Zhang, Qiang Liu, Xin Tong
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent. NeurIPS (2022)
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
Meta-Learning Divergences for Variational Inference. AISTATS (2021)
Ruqi Zhang, A. Feder Cooper, Christopher De Sa
Asymptotically Optimal Exact Minibatch Metropolis-Hastings. CoRR (2020)
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
Meta-Learning for Variational Inference. CoRR (2020)
Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning. ICLR (2020)
Ruqi Zhang, A. Feder Cooper, Christopher De Sa
Asymptotically Optimal Exact Minibatch Metropolis-Hastings. NeurIPS (2020)
Ruqi Zhang, A. Feder Cooper, Christopher De Sa
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC. CoRR (2020)
Ruqi Zhang, A. Feder Cooper, Christopher De Sa
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC. AISTATS (2020)
Ruqi Zhang, Christopher De Sa
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees. CoRR (2019)
Ruqi Zhang, Christopher De Sa
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees. NeurIPS (2019)
Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning. CoRR (2019)
Xiaochun Han, Yanni Fan, Haijun Zhao, Shijun Wang, Sisheng Tian, Hongyuan Zhang, Zhe Yang, Ruqi Zhang, Jing Zhang, Wei Shi
Acupoint Selection Rule Mining of Premature Ovarian Failure Treatment with Acupuncture and Moxibustion Based on the Data Analysis of Clinical Literature. BIBM (2018)
Ruqi Zhang, Zhiwu Lu
Large Scale Sparse Clustering. IJCAI (2016)
Ruqi Zhang, Zhirong Yang, Jukka Corander
Denoising Cluster Analysis. ICONIP (3) (2015)