From the 1 of 6 linked papers with an AI index.
4 papers · 1 filter
FunL2O: LLM-Guided Feature Function Design for Learning to Optimize
Bingheng Li, Junyang Cai, Yupeng Zhang +3
The paper presents FunL2O, a framework that uses large language models to automatically generate feature functions for learning-to-optimize systems, showing improved performance ov…
Learning to Shuffle: Block Reshuffling and Reversal Schemes for Stochastic Optimization
Lam M. Nguyen, Dzung T. Phan, Jayant Kalagnanam
Shuffling strategies for stochastic gradient descent (SGD), including incremental gradient, shuffle-once, and random reshuffling, are supported by rigorous convergence analyses for…
Cardinality-Regularized Hawkes-Granger Model
Tsuyoshi Idé, Georgios Kollias, Dzung T. Phan +1
We propose a new sparse Granger-causal learning framework for temporal event data. We focus on a specific class of point processes called the Hawkes process. We begin by pointing o…
TabularFM: An Open Framework For Tabular Foundational Models
Quan M. Tran, Suong N. Hoang, Lam M. Nguyen +2
Foundational models (FMs), pretrained on extensive datasets using self-supervised techniques, are capable of learning generalized patterns from large amounts of data. This reduces…