13 citations · 15 across the 8 of their papers we have counts for
8 papers
TimeLAVA: Learning-Agnostic Valuation for Time Series Data
Wenqin Liu, Weizhi Quan, Aoqi Zuo +5
Data valuation quantifies the intrinsic quality of individual samples to enable principled data curation, quality control, and robust learning. For time series in critical domains…
Adaptive Hard-Soft Physics-Informed Neural Networks for Robust Boundary-Constrained PDE Solving
Duc Tien Nguyen, Trinh Minh Tuan, Nguyen Duc Manh +2
Physics-informed neural networks (PINNs) provide an effective way to solve partial differential equations (PDEs) by embedding physical principles into the learning process. However…
On the Mechanisms of Collaborative Learning in VAE Recommenders
Tung-Long Vuong, Julien Monteil, Hien Dang +3
Variational Autoencoders (VAEs) are a powerful alternative to matrix factorization for recommendation. A common technique in VAE-based collaborative filtering (CF) consists in appl…
High Dimensional Bayesian Optimization using Lasso Variable Selection
Vu Viet Hoang, Hung The Tran, Sunil Gupta +1
Bayesian optimization (BO) is a leading method for optimizing expensive black-box optimization and has been successfully applied across various scenarios. However, BO suffers from…
MUSS: Multilevel Subset Selection for Relevance and Diversity
Vu Nguyen, Andrey Kan
The problem of relevant and diverse subset selection has a wide range of applications, including recommender systems and retrieval-augmented generation (RAG). For example, in recom…
Self-Supervision Improves Diffusion Models for Tabular Data Imputation
Yixin Liu, Thalaiyasingam Ajanthan, Hisham Husain +1
The ubiquity of missing data has sparked considerable attention and focus on tabular data imputation methods. Diffusion models, recognized as the cutting-edge technique for data ge…
SAVA: Scalable Learning-Agnostic Data Valuation
Samuel Kessler, Tam Le, Vu Nguyen
Selecting data for training machine learning models is crucial since large, web-scraped, real datasets contain noisy artifacts that affect the quality and relevance of individual d…
Rejection via Learning Density Ratios
Alexander Soen, Hisham Husain, Philip Schulz +1
Classification with rejection emerges as a learning paradigm which allows models to abstain from making predictions. The predominant approach is to alter the supervised learning pi…