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Greatest papers with code

VSQL: Variational Shadow Quantum Learning for Classification

15 Dec 2020PaddlePaddle/Quantum

Classification of quantum data is essential for quantum machine learning and near-term quantum technologies.

CLASSIFICATION HANDWRITTEN DIGIT RECOGNITION QUANTUM MACHINE LEARNING

Formal Verification of Piece-Wise Linear Feed-Forward Neural Networks

3 May 2017progirep/planet

We present a specialized verification algorithm that employs this approximation in a search process in which it infers additional node phases for the non-linear nodes in the network from partial node phase assignments, similar to unit propagation in classical SAT solving.

HANDWRITTEN DIGIT RECOGNITION

How Important is Weight Symmetry in Backpropagation?

17 Oct 2015willwx/sign-symmetry

Gradient backpropagation (BP) requires symmetric feedforward and feedback connections -- the same weights must be used for forward and backward passes.

 Ranked #1 on Handwritten Digit Recognition on MNIST (PERCENTAGE ERROR metric)

HANDWRITTEN DIGIT RECOGNITION IMAGE CLASSIFICATION

Large-scale Artificial Neural Network: MapReduce-based Deep Learning

9 Oct 2015sunkairan/MapReduce-Based-Deep-Learning

Faced with continuously increasing scale of data, original back-propagation neural network based machine learning algorithm presents two non-trivial challenges: huge amount of data makes it difficult to maintain both efficiency and accuracy; redundant data aggravates the system workload.

HANDWRITTEN DIGIT RECOGNITION

Frank-Wolfe Network: An Interpretable Deep Structure for Non-Sparse Coding

28 Feb 2018sunke123/FW-Net

We propose an interpretable deep structure namely Frank-Wolfe Network (F-W Net), whose architecture is inspired by unrolling and truncating the Frank-Wolfe algorithm for solving an $L_p$-norm constrained problem with $p\geq 1$.

HANDWRITTEN DIGIT RECOGNITION IMAGE DENOISING SUPER-RESOLUTION

LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence

20 Feb 2019yrahul3910/adaptive-lr-dnn

In this paper, we propose a novel method to compute the learning rate for training deep neural networks with stochastic gradient descent.

HANDWRITTEN DIGIT RECOGNITION OBJECT DETECTION

MNIST-MIX: A Multi-language Handwritten Digit Recognition Dataset

8 Apr 2020jwwthu/MNIST-MIX

In this letter, we contribute a multi-language handwritten digit recognition dataset named MNIST-MIX, which is the largest dataset of the same type in terms of both languages and data samples.

HANDWRITTEN DIGIT RECOGNITION IMBALANCED CLASSIFICATION

Bangla Handwritten Digit Recognition and Generation

14 Mar 2021fahim-sikder/Bangla-Digit-Generation-GAN

Handwritten digit or numeral recognition is one of the classical issues in the area of pattern recognition and has seen tremendous advancement because of the recent wide availability of computing resources.

HANDWRITTEN DIGIT RECOGNITION