NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.

Related tags

Deep Learningmachine-learningdeep-learningoptimizationmathmatical-software
Overview

NCVX

Example screenshot

NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.

Please check https://ncvx.org for detailed instructions (introduction, installation, settings, examples...).

Brief Introduction

Optimizing nonconvex (NCVX) problems, especially those nonsmooth and constrained, is an essential part of machine learning and deep learning. But it is hard to reliably solve this type of problems without optimization expertise. Existing general-purpose NCVX optimization packages are powerful, but typically cannot handle nonsmoothness. GRANSO is among the first packages targeting NCVX, nonsmooth, constrained problems. However, it has several limitations such as the lack of auto-differentiation and GPU acceleration, which preclude the potential broad deployment by non-experts. To lower the technical barrier for the machine learning community, we revamp GRANSO into a user-friendly and scalable python package named NCVX, featuring auto-differentiation, GPU acceleration, tensor input, scalable QP solver, and zero dependency on proprietary packages. As a highlight, NCVX can solve general constrained deep learning problems, the first of its kind.

Update Logs

v1.1.1: Multiple examples added: unconstrained DL, feasibility problem, sphere manifold.

v1.1.0: L-BFGS Added.

v1.0.0: Initial release of NCVX. Main features: auto-differentiation, GPU acceleration, tensor input, scalable QP solver, and zero dependency on proprietary packages.

Acknowledgements

We would like to thank the GRANSO developers. This work was supported by UMII Seed Grant Program and NSF CMMI 2038403.

Contact

Codes written by Buyun Liang (https://buyunliang.org). Questions or bug reports please send email to Buyun Liang, [email protected].

Thanks to bug reporters:

You might also like...
Racing line optimization algorithm in python that uses Particle Swarm Optimization.
Racing line optimization algorithm in python that uses Particle Swarm Optimization.

Racing Line Optimization with PSO This repository contains a racing line optimization algorithm in python that uses Particle Swarm Optimization. Requi

Parsa Dahesh 6 Dec 14, 2022
mlpack: a scalable C++ machine learning library --
mlpack: a scalable C++ machine learning library --

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

mlpack 4.2k Jan 9, 2023
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l

Distributed (Deep) Machine Learning Community 23.6k Dec 31, 2022
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l

Distributed (Deep) Machine Learning Community 20.6k Feb 13, 2021
A simple and lightweight genetic algorithm for optimization of any machine learning model

geneticml This package contains a simple and lightweight genetic algorithm for optimization of any machine learning model. Installation Use pip to ins

Allan Barcelos 8 Aug 10, 2022
A Machine Teaching Framework for Scalable Recognition

MEMORABLE This repository contains the source code accompanying our ICCV 2021 paper. A Machine Teaching Framework for Scalable Recognition Pei Wang, N

null 2 Dec 8, 2021
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose

Erik Linder-Norén 21.8k Jan 9, 2023
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

This is the Vowpal Wabbit fast online learning code. Why Vowpal Wabbit? Vowpal Wabbit is a machine learning system which pushes the frontier of machin

Vowpal Wabbit 8.1k Jan 6, 2023
NUANCED is a user-centric conversational recommendation dataset that contains 5.1k annotated dialogues and 26k high-quality user turns.
NUANCED is a user-centric conversational recommendation dataset that contains 5.1k annotated dialogues and 26k high-quality user turns.

NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions Overview NUANCED is a user-centric conversational recommen

Facebook Research 18 Dec 28, 2021
Releases(v1.1.1)
Owner
SUN Group @ UMN
SUN Group @ UMN
GitHub Repository https://ncvx.org
SigOpt wrappers for scikit-learn methods

SigOpt + scikit-learn Interfacing This package implements useful interfaces and wrappers for using SigOpt and scikit-learn together Getting Started In

SigOpt 73 Sep 30, 2022
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance

Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.

Muhan Zhang 38 Jan 05, 2023
Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow.

custom-cnn-fashion-mnist Creating a custom CNN hypertunned architeture for the Fashion MNIST dataset with Python, Keras and Tensorflow. The following

Danielle Almeida 1 Mar 05, 2022
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p

Rishikesh (ऋषिकेश) 31 Dec 08, 2022
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks

Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks

Jina AI 794 Dec 31, 2022
A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Aboleth A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation [1] with stochastic gradient variational Bayes

Gradient Institute 127 Dec 12, 2022
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch

Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c

Phil Wang 272 Dec 23, 2022
Code repository for the paper Computer Vision User Entity Behavior Analytics

Computer Vision User Entity Behavior Analytics Code repository for "Computer Vision User Entity Behavior Analytics" Code Description dataset.csv As di

Sameer Khanna 2 Aug 20, 2022
Implementation of Multistream Transformers in Pytorch

Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi

Phil Wang 47 Jul 26, 2022
Implementation of Sequence Generative Adversarial Nets with Policy Gradient

SeqGAN Requirements: Tensorflow r1.0.1 Python 2.7 CUDA 7.5+ (For GPU) Introduction Apply Generative Adversarial Nets to generating sequences of discre

Lantao Yu 2k Dec 29, 2022
Official implementation of CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21

CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different

Sunghwan Hong 120 Jan 04, 2023
Video Frame Interpolation without Temporal Priors (a general method for blurry video interpolation)

Video Frame Interpolation without Temporal Priors (NeurIPS2020) [Paper] [video] How to run Prerequisites NVIDIA GPU + CUDA 9.0 + CuDNN 7.6.5 Pytorch 1

YoujianZhang 31 Sep 04, 2022
"Inductive Entity Representations from Text via Link Prediction" @ The Web Conference 2021

Inductive entity representations from text via link prediction This repository contains the code used for the experiments in the paper "Inductive enti

Daniel Daza 45 Jan 09, 2023
Implementation of "RaScaNet: Learning Tiny Models by Raster-Scanning Image" from CVPR 2021.

RaScaNet: Learning Tiny Models by Raster-Scanning Images Deploying deep convolutional neural networks on ultra-low power systems is challenging, becau

SAIT (Samsung Advanced Institute of Technology) 5 Dec 26, 2022
Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks

Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks by Ángel López García-Arias, Masanori Hashimoto, Masato Motomura, and J

Ángel López García-Arias 4 May 19, 2022
🦕 NanoSaur is a little tracked robot ROS2 enabled, made for an NVIDIA Jetson Nano

🦕 nanosaur NanoSaur is a little tracked robot ROS2 enabled, made for an NVIDIA Jetson Nano Website: nanosaur.ai Do you need an help? Discord For tech

NanoSaur 162 Dec 09, 2022
Official implementation of "SinIR: Efficient General Image Manipulation with Single Image Reconstruction" (ICML 2021)

SinIR (Official Implementation) Requirements To install requirements: pip install -r requirements.txt We used Python 3.7.4 and f-strings which are in

47 Oct 11, 2022
Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval.

DARP-SBIR Intro This repository contains the source code implementation for ICDM submission paper Deep Reinforced Attention Regression for Partial Ske

2 Jan 09, 2022
Natural Intelligence is still a pretty good idea.

Human Learn Machine Learning models should play by the rules, literally. Project Goal Back in the old days, it was common to write rule-based systems.

vincent d warmerdam 641 Dec 26, 2022
A library for using chemistry in your applications

Chemistry in python Resources Used The following items are not made by me! Click the words to go to the original source Periodic Tab Json - Used in -

Tech Penguin 28 Dec 17, 2021