2 citations · 2 across the 2 of their papers we have counts for
4 papers
Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential
Yuping Zheng, Andrew Lamperski
Stochastic gradient descent (SGD) is the main algorithm behind a large body of work in machine learning. In many cases, constraints are enforced via projections, leading to project…
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Guorui Zheng, Xidong Wang, Juhao Liang +3
Adapting medical Large Language Models to local languages can reduce barriers to accessing healthcare services, but data scarcity remains a significant challenge, particularly for…
Non-Asymptotic Analysis of Classical Spectrum Estimators with -mixing Time-series Data
Yuping Zheng, Andrew Lamperski
Spectral estimation is a fundamental problem for time series analysis, which is widely applied in economics, speech analysis, seismology, and control systems. The asymptotic conver…
From fat droplets to floating forests: cross-domain transfer learning using a PatchGAN-based segmentation model
Kameswara Bharadwaj Mantha, Ramanakumar Sankar, Yuping Zheng +11
Many scientific domains gather sufficient labels to train machine algorithms through human-in-the-loop techniques provided by the Zooniverse.org citizen science platform. As the ra…