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04/20/2022
Search-based Methods for Multi-Cloud Configuration
Multi-cloud computing has become increasingly popular with enterprises l...
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11/16/2020
Towards a General Framework for ML-based Self-tuning Databases
Machine learning (ML) methods have recently emerged as an effective way ...
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06/17/2020
MixBoost: A Heterogeneous Boosting Machine
Modern gradient boosting software frameworks, such as XGBoost and LightG...
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06/12/2020
Differentially Private Stochastic Coordinate Descent
In this paper we tackle the challenge of making the stochastic coordinat...
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11/18/2019
SySCD: A System-Aware Parallel Coordinate Descent Algorithm
In this paper we propose a novel parallel stochastic coordinate descent ...
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10/15/2019
Breadth-first, Depth-next Training of Random Forests
In this paper we analyze, evaluate, and improve the performance of train...
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09/16/2019
Learning to Tune XGBoost with XGBoost
In this short paper we investigate whether meta-learning techniques can ...
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09/16/2019
Weighted Sampling for Combined Model Selection and Hyperparameter Tuning
The combined algorithm selection and hyperparameter tuning (CASH) proble...
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09/11/2019
Addressing Algorithmic Bottlenecks in Elastic Machine Learning with Chicle
Distributed machine learning training is one of the most common and impo...
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06/08/2019
5 Parallel Prism: A topology for pipelined implementations of convolutional neural networks using computational memory
In-memory computing is an emerging computing paradigm that could enable ...
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03/22/2019
Sampling Acquisition Functions for Batch Bayesian Optimization
This paper presents Acquisition Thompson Sampling (ATS), a novel algorit...
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11/06/2018
Elastic CoCoA: Scaling In to Improve Convergence
In this paper we experimentally analyze the convergence behavior of CoCo...
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11/05/2018
Parallel training of linear models without compromising convergence
In this paper we analyze, evaluate, and improve the performance of train...
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09/12/2018
Benchmarking and Optimization of Gradient Boosted Decision Tree Algorithms
Gradient boosted decision trees (GBDTs) have seen widespread adoption in...
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03/16/2018
Snap Machine Learning
We describe an efficient, scalable machine learning library that enables...
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11/20/2017
Linear-Complexity Relaxed Word Mover's Distance with GPU Acceleration
The amount of unstructured text-based data is growing every day. Queryin...
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08/17/2017