2 citations · 3 across the 8 of their papers we have counts for
6 papers · 1 filter
Performance Prediction for Large Systems via Text-to-Text Regression
Yash Akhauri, Bryan Lewandowski, Cheng-Hsi Lin +7
In many industries, predicting metric outcomes of large systems is a fundamental problem, driven largely by traditional tabular regression. However, such methods struggle on comple…
Decoding-based Regression
Xingyou Song, Dara Bahri
Language models have recently been shown capable of performing regression wherein numeric predictions are represented as decoded strings. In this work, we provide theoretical groun…
Understanding LLM Embeddings for Regression
Eric Tang, Bangding Yang, Xingyou Song
With the rise of large language models (LLMs) for flexibly processing information as strings, a natural application is regression, specifically by preprocessing string representati…
Language Model Embeddings Can Be Sufficient for Bayesian Optimization
Tung Nguyen, Qiuyi Zhang, Bangding Yang +6
Bayesian Optimization is ubiquitous in experimental design and black-box optimization for improving search efficiency. However, most existing approaches rely on regression models w…
The Vizier Gaussian Process Bandit Algorithm
Xingyou Song, Qiuyi Zhang, Chansoo Lee +8
Google Vizier has performed millions of optimizations and accelerated numerous research and production systems at Google, demonstrating the success of Bayesian optimization as a la…
Position: Leverage Foundational Models for Black-Box Optimization
Xingyou Song, Yingtao Tian, Robert Tjarko Lange +3
Undeniably, Large Language Models (LLMs) have stirred an extraordinary wave of innovation in the machine learning research domain, resulting in substantial impact across diverse fi…