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09/08/2023
Matching Table Metadata with Business Glossaries Using Large Language Models
Enterprises often own large collections of structured data in the form o...
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03/02/2023
A Vision for Semantically Enriched Data Science
The recent efforts in automation of machine learning or data science has...
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05/16/2022
A Survey on Semantics in Automated Data Science
Data Scientists leverage common sense reasoning and domain knowledge to ...
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02/16/2022
Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm Analysis
We address the relatively unexplored problem of hyper-parameter optimiza...
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12/15/2021
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning
We address the relatively unexplored problem of hyper-parameter optimiza...
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01/07/2021
How Much Automation Does a Data Scientist Want?
Data science and machine learning (DS/ML) are at the heart of the recent...
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06/17/2020
Solving Constrained CASH Problems with ADMM
The CASH problem has been widely studied in the context of automated con...
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10/22/2019
How can AI Automate End-to-End Data Science?
Data science is labor-intensive and human experts are scarce but heavily...
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09/05/2019
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI
The rapid advancement of artificial intelligence (AI) is changing our li...
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05/01/2019
Automated Machine Learning via ADMM
We study the automated machine learning (AutoML) problem of jointly sele...
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03/02/2019
Automating Predictive Modeling Process using Reinforcement Learning
Building a good predictive model requires an array of activities such as...
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01/17/2019
NeuNetS: An Automated Synthesis Engine for Neural Network Design
Application of neural networks to a vast variety of practical applicatio...
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11/16/2017
Neurology-as-a-Service for the Developing World
Electroencephalography (EEG) is an extensively-used and well-studied tec...
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09/21/2017
Feature Engineering for Predictive Modeling using Reinforcement Learning
Feature engineering is a crucial step in the process of predictive model...
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05/23/2017
An effective algorithm for hyperparameter optimization of neural networks
A major challenge in designing neural network (NN) systems is to determi...
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12/31/2015
Selecting Near-Optimal Learners via Incremental Data Allocation
We study a novel machine learning (ML) problem setting of sequentially a...
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03/06/2012
