421 citations · 3.9k across the 201 of their papers we have counts for
226 papers
Generalization of Transformer-Based Neural Quantum States via In-Context Learning
Zhen Qin, Qing Qu, Alfred O. Hero
Neural quantum states based on modern deep learning architectures have emerged as powerful representations for quantum many-body systems. In particular, Transformer-based neural qu…
Iterative Sketching for Secure Coded Regression
Neophytos Charalambides, Hessam Mahdavifar, Mert Pilanci +1
Linear regression is a fundamental and primitive problem in supervised machine learning, with applications ranging from epidemiology to finance. In this work, we propose methods fo…
Gradient Coding with Iterative Block Leverage Score Sampling
Neophytos Charalambides, Mert Pilanci, Alfred Hero
We generalize the leverage score sampling sketch for -subspace embeddings, to accommodate sampling subsets of the transformed data, so that the sketching approach is approp…
Minimum-Risk Recalibration of Classifiers
Zeyu Sun, Dogyoon Song, Alfred Hero
Recalibrating probabilistic classifiers is vital for enhancing the reliability and accuracy of predictive models. Despite the development of numerous recalibration algorithms, ther…
Graph Sparsification by Approximate Matrix Multiplication
Neophytos Charalambides, Alfred O. Hero
Graphs arising in statistical problems, signal processing, large networks, combinatorial optimization, and data analysis are often dense, which causes both computational and storag…
Robustness-preserving Lifelong Learning via Dataset Condensation
Jinghan Jia, Yihua Zhang, Dogyoon Song +2
Lifelong learning (LL) aims to improve a predictive model as the data source evolves continuously. Most work in this learning paradigm has focused on resolving the problem of 'cata…