Ensemble Learning

310 papers with code • 1 benchmarks • 3 datasets

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Libraries

Use these libraries to find Ensemble Learning models and implementations

Most implemented papers

Gossip Learning with Linear Models on Fully Distributed Data

tribler/trustchain-superapp 7 Sep 2011

Machine learning over fully distributed data poses an important problem in peer-to-peer (P2P) applications.

Predicting the direction of stock market prices using random forest

jmartinezheras/reproduce-stock-market-direction-random-forests 29 Apr 2016

In this paper, we propose a novel way to minimize the risk of investment in stock market by predicting the returns of a stock using a class of powerful machine learning algorithms known as ensemble learning.

Masksembles for Uncertainty Estimation

nikitadurasov/masksembles CVPR 2021

Our central intuition is that there is a continuous spectrum of ensemble-like models of which MC-Dropout and Deep Ensembles are extreme examples.

Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding

namisan/mt-dnn 20 Apr 2019

This paper explores the use of knowledge distillation to improve a Multi-Task Deep Neural Network (MT-DNN) (Liu et al., 2019) for learning text representations across multiple natural language understanding tasks.

DebiasedDTA: A Framework for Improving the Generalizability of Drug-Target Affinity Prediction Models

boun-tabi/debiaseddta-reproduce 4 Jul 2021

Here, we present DebiasedDTA, a novel drug-target affinity (DTA) prediction model training framework that addresses dataset biases to improve the generalizability of affinity prediction models.

Representation Topology Divergence: A Method for Comparing Neural Network Representations

ilyatrofimov/rtd 31 Dec 2021

Comparison of data representations is a complex multi-aspect problem that has not enjoyed a complete solution yet.

Deep Ensemble Learning with Frame Skipping for Face Anti-Spoofing

Usman1021/DLE 6 Jul 2023

Face presentation attacks (PA), also known as spoofing attacks, pose a substantial threat to biometric systems that rely on facial recognition systems, such as access control systems, mobile payments, and identity verification systems.

Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning

scikit-learn-contrib/imbalanced-learn 21 Sep 2016

Imbalanced-learn is an open-source python toolbox aiming at providing a wide range of methods to cope with the problem of imbalanced dataset frequently encountered in machine learning and pattern recognition.

An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy

cpapadimitriou/Click-Through-Rate-prediction 4 Nov 2017

In this paper, we provide a holistic view of Etsy's promoted listings' CTR prediction system and propose an ensemble learning approach which is based on historical or behavioral signals for older listings as well as content-based features for new listings.

Unsupervised Evaluation and Weighted Aggregation of Ranked Predictions

learn-ensemble/R-SUMMA 13 Feb 2018

Learning algorithms that aggregate predictions from an ensemble of diverse base classifiers consistently outperform individual methods.