Found 4006 results, showing the newest relevant preprints. Sort by relevancy only.Update me on new preprints

XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning

The proposed framework combines the strengths of both supervised and unsupervised machine learning methods by creating a hybrid approach that exploits each of their individual performance capabilities in outlier detection. Expand abstract.
58 days ago
4/10 relevant
arXiv

A Machine Learning Approach to Adaptive Robust Utility Maximization and Hedging

We propose a novel machine learning approach that solves for the local saddle-point at a chosen set of inputs and then uses a nonparametric (Gaussian process) regression to obtain a functional representation of the value function. Expand abstract.
58 days ago
10/10 relevant
arXiv

Machine learning on drug-specific data to predict small molecule teratogenicity

Using unsupervised and supervised machine learning, our model probes all small molecules with known structure and teratogenicity data published in research-amenable formats to identify patterns among structural, meta-structural, and in vitro bioactivity data for each drug and its teratogenicity score. Expand abstract.
58 days ago
10/10 relevant
bioRxiv

A machine learning based approach to the segmentation of micro CT data in archaeological and evolutionary sciences

We demonstrate that Trainable Weka Segmentation can provide a fast and robust method for segmentation and is as effective as other leading-edge machine learning segmentation techniques. Expand abstract.
59 days ago
10/10 relevant
bioRxiv

Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019

Machine Learning (ML) researchers came up with various models and a vast number of studies have been published accordingly. Expand abstract.
59 days ago
4/10 relevant
arXiv

Machine Learning Predicts New Anti-CRISPR Proteins

Here, we describe AcRanker, a machine learning based method for identifying new potential anti-CRISPRs directly from proteomes using protein sequence information only. Expand abstract.
60 days ago
10/10 relevant
bioRxiv

Predictive engineering and optimization of tryptophan metabolism in yeast through a combination of mechanistic and machine learning models

Based on a single high-throughput data-generation iteration, this study highlights the power of combining mechanistic and machine learning models to enhance their predictive power and effectively direct metabolic engineering efforts. Expand abstract.
60 days ago
10/10 relevant
bioRxiv

FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions

FairPrep is based on a developer-centered design, and helps data scientists follow best practices in software engineering and machine learning. Expand abstract.
60 days ago
4/10 relevant
arXiv

Computer Systems Have 99 Problems, Let's Not Make Machine Learning Another One

We also discuss reproducibility as a key requirement for sustainable machine learning systems, and leads to pursuing it. Expand abstract.
60 days ago
7/10 relevant
arXiv

Optimization of heterogeneous ternary Li3PO4-Li3BO3-Li2SO4 mixture for Li-ion conductivity by machine learning

Although the mechanism enhancing Li-ion conductivity is not simple, our results demonstrate the effectiveness of machine learning for the development of materials. Expand abstract.
60 days ago
10/10 relevant
arXiv