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Regression

816 papers with code · Music

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Greatest papers with code

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

14 Mar 2016tensorflow/tensorflow

TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms.

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Black-box $α$-divergence Minimization

10 Nov 2015tensorflow/models

Black-box alpha (BB-$\alpha$) is a new approximate inference method based on the minimization of $\alpha$-divergences.

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Weight Uncertainty in Neural Networks

20 May 2015tensorflow/models

We introduce a new, efficient, principled and backpropagation-compatible algorithm for learning a probability distribution on the weights of a neural network, called Bayes by Backprop.

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Scikit-learn: Machine Learning in Python

2 Jan 2012scikit-learn/scikit-learn

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.

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Automatic Differentiation in PyTorch

NIPS 2017 2017 pytorch/pytorch

In this article, we describe an automatic differentiation module of PyTorch — a library designed to enable rapid research on machine learning models.

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Caffe: Convolutional Architecture for Fast Feature Embedding

20 Jun 2014BVLC/caffe

The framework is a BSD-licensed C++ library with Python and MATLAB bindings for training and deploying general-purpose convolutional neural networks and other deep models efficiently on commodity architectures.

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MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

3 Dec 2015apache/incubator-mxnet

This paper describes both the API design and the system implementation of MXNet, and explains how embedding of both symbolic expression and tensor operation is handled in a unified fashion.

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XGBoost: A Scalable Tree Boosting System

9 Mar 2016dmlc/xgboost

In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges.

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CNTK: Microsoft's Open-Source Deep-Learning Toolkit

ACM SIGKDD 2016 Microsoft/CNTK

This tutorial will introduce the Computational Network Toolkit, or CNTK, Microsoft's cutting-edge open-source deep-learning toolkit for Windows and Linux.

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Theano: A Python framework for fast computation of mathematical expressions

9 May 2016Theano/Theano

Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements.

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