45 citations · 168 across the 25 of their papers we have counts for
14 papers · 1 filter
H-SPLID: HSIC-based Saliency Preserving Latent Information Decomposition
Lukas Miklautz, Chengzhi Shi, Andrii Shkabrii +5
We introduce H-SPLID, a novel algorithm for learning salient feature representations through the explicit decomposition of salient and non-salient features into separate spaces. We…
Spectral Survival Analysis
Chengzhi Shi, Stratis Ioannidis
Survival analysis is widely deployed in a diverse set of fields, including healthcare, business, ecology, etc. The Cox Proportional Hazard (CoxPH) model is a semi-parametric model…
Dependency-aware Maximum Likelihood Estimation for Active Learning
Beyza Kalkanli, Tales Imbiriba, Stratis Ioannidis +2
Active learning aims to efficiently build a labeled training set by strategically selecting samples to query labels from annotators. In this sequential process, each sample acquisi…
Learning Set Functions with Implicit Differentiation
Gözde Özcan, Chengzhi Shi, Stratis Ioannidis
Ou et al. (2022) introduce the problem of learning set functions from data generated by a so-called optimal subset oracle. Their approach approximates the underlying utility functi…
Pruning Adversarially Robust Neural Networks without Adversarial Examples
Tong Jian, Zifeng Wang, Yanzhi Wang +2
Adversarial pruning compresses models while preserving robustness. Current methods require access to adversarial examples during pruning. This significantly hampers training effici…
SparCL: Sparse Continual Learning on the Edge
Zifeng Wang, Zheng Zhan, Yifan Gong +7
Existing work in continual learning (CL) focuses on mitigating catastrophic forgetting, i.e., model performance deterioration on past tasks when learning a new task. However, the t…