2 citations · 2 across the 10 of their papers we have counts for
10 papers
C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs
Jiameng Li, Han Zhou, Matthew B. Blaschko
Multimodal large language models (MLLMs) require huge memory and computational costs, which limits their practical deployment. Post-training quantization (PTQ) techniques offer an…
Bandwidth Selection in Kernel Density Estimation for Model Calibration
Han Zhou, Teodora Popordanoska, Matthew Blaschko
As deep learning models are increasingly deployed in high-stakes applications, providing well-calibrated uncertainty estimates has become as critical as achieving high predictive a…
Learning Longitudinal Health Representations from EHR and Wearable Data
Yuanyun Zhang, Han Zhou, Li Feng +2
Foundation models trained on electronic health records show strong performance on many clinical prediction tasks but are limited by sparse and irregular documentation. Wearable dev…
Bayesian Optimization over Bounded Domains with the Beta Product Kernel
Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko +1
Bayesian optimization with Gaussian processes (GP) is commonly used to optimize black-box functions. The Matérn and the Radial Basis Function (RBF) covariance functions are used fr…
Revisiting Reweighted Risk for Calibration: AURC, Focal, and Inverse Focal Loss
Han Zhou, Sebastian G. Gruber, Teodora Popordanoska +1
Several variants of reweighted risk functionals, such as focal loss, inverse focal loss, and the Area Under the Risk Coverage Curve (AURC), have been proposed for improving model c…
A Reinforcement Learning Method to Factual and Counterfactual Explanations for Session-based Recommendation
Han Zhou, Hui Fang, Zhu Sun +1
Session-based Recommendation (SR) systems have recently achieved considerable success, yet their complex, "black box" nature often obscures why certain recommendations are made. Ex…
A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators
Han Zhou, Jordy Van Landeghem, Teodora Popordanoska +1
The selective classifier (SC) has been proposed for rank based uncertainty thresholding, which could have applications in safety critical areas such as medical diagnostics, autonom…
Diversity-Driven View Subset Selection for Indoor Novel View Synthesis
Zehao Wang, Han Zhou, Matthew B. Blaschko +2
Novel view synthesis of indoor scenes can be achieved by capturing a monocular video sequence of the environment. However, redundant information caused by artificial movements in t…
CVTN: Cross Variable and Temporal Integration for Time Series Forecasting
Han Zhou, Yuntian Chen
In multivariate time series forecasting, the Transformer architecture encounters two significant challenges: effectively mining features from historical sequences and avoiding over…
A Corrected Expected Improvement Acquisition Function Under Noisy Observations
Han Zhou, Xingchen Ma, Matthew B Blaschko
Sequential maximization of expected improvement (EI) is one of the most widely used policies in Bayesian optimization because of its simplicity and ability to handle noisy observat…