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adam_implementation

Implementation of ADAM optimizer

anmlzoo

High-performance automata-processing engines are traditionally evaluated using a limited set of regular expression rulesets. While regular expression rulesets are valid real-world examples of use cases for automata processing, they represent a small proportion of all use cases for automata-based computing. With the recent availability of architectures and software frameworks for automata processing, many new applications have been found to benefit from automata processing. These show a wide variety of characteristics that differ from prior, popular regular-expression benchmarks, and these should be considered when designing new systems for automata processing. This paper presents ANMLZoo, a benchmark repository for automata-based applications as well as automata engines for both von-Neumann and reconfigurable data flow architectures.

asyn_kernel_svm

Asynchronous Parallel Kernel SVM on multicore shared memory system

atac_dnase_pipelines

ATAC-seq and DNase-seq processing pipeline

awesome-deep-learning-papers

The most cited deep learning papers

benchmarking-tools

Repository for the GA4GH Benchmarking Team work developing standardized benchmarking methods for germline small variant calls

bhattacharyya-distance

Computes the Bhattacharyya distance for feature selection in machine learning.

buckshot

An R interface to "shotgun", a parallel lasso and sparse logistic regression solver written in C++

caffe

Caffe: a fast open framework for deep learning.

calculator

Windows Calculator: A simple yet powerful calculator that ships with Windows

char-rnn

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

char-rnn-tensorflow

Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow

class-imbalance

Dealing with class imbalance problem in machine learning. Synthetic oversampling(SMOTE, ADASYN).

classification

Classification

classification-and-regression-tree

Implemented the Classification and Regression Trees Algo in pure python to classify authentic banknotes.

clustersvdd

Cluster Support Vector Data Description

cnnimageretrieval-pytorch

CNN Image Retrieval in PyTorch: Training and evaluating CNNs for Image Retrieval in PyTorch

conditional-gan

Tensorflow implement for Conditional convolutional adversarial networks.

contents

Table of contents generator.

cs181-lectures

cuda

GPU-accelerated LIBSVM is a modification of the original LIBSVM that exploits the CUDA framework to significantly reduce processing time while producing identical results. The functionality and interface of LIBSVM remains the same. The modifications were done in the kernel computation, that is now performed using the GPU.

dc_svm

http://www.cs.utexas.edu/~cjhsieh/dcsvm/

debymoto

deep-belief-network

deepmotif

Deep Motif (ICLR16)/ Deep Motif Dashboard (PSB17): Visualizing Genomic Sequence Classifications

developer-roadmap

Roadmap to becoming a web developer in 2017

dictol

DICTOL - A Dictionary Learning Toolbox in Matlab and Python

dissecting-reinforcement-learning

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

distributed-ksvm

Distributed training for kernel SVM (PBM)

dlx