112 citations · 144 across the 40 of their papers we have counts for
6 papers · 1 filter
Entropy-MCMC: Sampling from Flat Basins with Ease
Bolian Li, Ruqi Zhang
Bayesian deep learning counts on the quality of posterior distribution estimation. However, the posterior of deep neural networks is highly multi-modal in nature, with local modes…
Rethinking Data Distillation: Do Not Overlook Calibration
Dongyao Zhu, Bowen Lei, Jie Zhang +4
Neural networks trained on distilled data often produce over-confident output and require correction by calibration methods. Existing calibration methods such as temperature scalin…
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging
Tunazzina Islam, Ruqi Zhang, Dan Goldwasser
Climate change is the defining issue of our time, and we are at a defining moment. Various interest groups, social movement organizations, and individuals engage in collective acti…
Long-tailed Classification from a Bayesian-decision-theory Perspective
Bolian Li, Ruqi Zhang
Long-tailed classification poses a challenge due to its heavy imbalance in class probabilities and tail-sensitivity risks with asymmetric misprediction costs. Recent attempts have…
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference
Wanrong Zhang, Ruqi Zhang
Bayesian inference provides a principled framework for learning from complex data and reasoning under uncertainty. It has been widely applied in machine learning tasks such as medi…
Calibrating the Rigged Lottery: Making All Tickets Reliable
Bowen Lei, Ruqi Zhang, Dongkuan Xu +1
Although sparse training has been successfully used in various resource-limited deep learning tasks to save memory, accelerate training, and reduce inference time, the reliability…