28 citations · 84 across the 12 of their papers we have counts for
8 papers · 1 filter
Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis
Yi Zhou, Parikshit Ram, Theodoros Salonidis +3
We address the relatively unexplored problem of hyper-parameter optimization (HPO) for federated learning (FL-HPO). We introduce Federated Loss SuRface Aggregation (FLoRA), a gener…
AutoAI-TS: AutoAI for Time Series Forecasting
Syed Yousaf Shah, Dhaval Patel, Long Vu +10
A large number of time series forecasting models including traditional statistical models, machine learning models and more recently deep learning have been proposed in the literat…
How Much Automation Does a Data Scientist Want?
Dakuo Wang, Q. Vera Liao, Yunfeng Zhang +5
Data science and machine learning (DS/ML) are at the heart of the recent advancements of many Artificial Intelligence (AI) applications. There is an active research thread in AI, \…
Solving Constrained CASH Problems with ADMM
Parikshit Ram, Sijia Liu, Deepak Vijaykeerthi +5
The CASH problem has been widely studied in the context of automated configurations of machine learning (ML) pipelines and various solvers and toolkits are available. However, CASH…
Optimal Exploitation of Clustering and History Information in Multi-Armed Bandit
Djallel Bouneffouf, Srinivasan Parthasarathy, Horst Samulowitz +1
We consider the stochastic multi-armed bandit problem and the contextual bandit problem with historical observations and pre-clustered arms. The historical observations can contain…
An ADMM Based Framework for AutoML Pipeline Configuration
Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy +6
We study the AutoML problem of automatically configuring machine learning pipelines by jointly selecting algorithms and their appropriate hyper-parameters for all steps in supervis…