733 citations
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12 papers · 1 filter
A Two-Timescale Approach for Wireless Federated Learning with Parameter Freezing and Power Control
Jinhao Ouyang, Yuan Liu, Hang Liu
Federated learning (FL) enables distributed devices to train a shared machine learning (ML) model collaboratively while protecting their data privacy. However, the resource-limited…
ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
Junjie Yin, Jiahao Dong, Yingheng Wang +2
We propose a memory-efficient finetuning algorithm for large language models (LLMs) that supports finetuning LLMs with 65B parameters in 2/3/4-bit precision on as little as one 24G…
An improved column-generation-based matheuristic for learning classification trees
Krunal Kishor Patel, Guy Desaulniers, Andrea Lodi
Decision trees are highly interpretable models for solving classification problems in machine learning (ML). The standard ML algorithms for training decision trees are fast but gen…
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
Suraj Rajendran, Weishen Pan, Mert R. Sabuncu +3
Machine learning (ML) in healthcare presents numerous opportunities for enhancing patient care, population health, and healthcare providers' workflows. However, the real-world clin…
Contextual Bandits with Budgeted Information Reveal
Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu +1
Contextual bandit algorithms are commonly used in digital health to recommend personalized treatments. However, to ensure the effectiveness of the treatments, patients are often re…
GLACIAL: Granger and Learning-based Causality Analysis for Longitudinal Imaging Studies
Minh Nguyen, Gia H. Ngo, Mert R. Sabuncu
The Granger framework is useful for discovering causal relations in time-varying signals. However, most Granger causality (GC) methods are developed for densely sampled timeseries…