Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning

01/12/2020
by   Yao Zhang, et al.
0

An essential problem in automated machine learning (AutoML) is that of model selection. A unique challenge in the sequential setting is the fact that the optimal model itself may vary over time, depending on the distribution of features and labels available up to each point in time. In this paper, we propose a novel Bayesian optimization (BO) algorithm to tackle the challenge of model selection in this setting. This is accomplished by treating the performance at each time step as its own black-box function. In order to solve the resulting multiple black-box function optimization problem jointly and efficiently, we exploit potential correlations among black-box functions using deep kernel learning (DKL). To the best of our knowledge, we are the first to formulate the problem of stepwise model selection (SMS) for sequence prediction, and to design and demonstrate an efficient joint-learning algorithm for this purpose. Using multiple real-world datasets, we verify that our proposed method outperforms both standard BO and multi-objective BO algorithms on a variety of sequence prediction tasks.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/29/2019

Lifelong Bayesian Optimization

Automatic Machine Learning (Auto-ML) systems tackle the problem of autom...
research
08/01/2023

Predictive Modeling through Hyper-Bayesian Optimization

Model selection is an integral problem of model based optimization techn...
research
12/07/2020

Adaptive Local Bayesian Optimization Over Multiple Discrete Variables

In the machine learning algorithms, the choice of the hyperparameter is ...
research
10/25/2018

Model Selection using Multi-Objective Optimization

Choices in scientific research and management require balancing multiple...
research
01/28/2019

Inference after black box selection

We consider the problem of inference for parameters selected to report o...
research
03/17/2018

Multi-device, Multi-tenant Model Selection with GP-EI

Bayesian optimization is the core technique behind the emergence of Auto...

Please sign up or login with your details

Forgot password? Click here to reset