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Found 5 papers, 3 papers with code
Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework
Unlike existing methods that use the same quantization scheme for all weights, we propose the first solution that applies different quantization schemes for different rows of the weight matrix.
NITI: Training Integer Neural Networks Using Integer-only Arithmetic
While integer arithmetic has been widely adopted for improved performance in deep quantized neural network inference, training remains a task primarily executed using floating point arithmetic.
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers
We present a novel network pruning algorithm called Dynamic Sparse Training that can jointly find the optimal network parameters and sparse network structure in a unified optimization process with trainable pruning thresholds.
High-dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction
We consider the problem of high-dimensional light field reconstruction and develop a learning-based framework for spatial and angular super-resolution.
Consistency Analysis for the Doubly Stochastic Dirichlet Process
This technical report proves components consistency for the Doubly Stochastic Dirichlet Process with exponential convergence of posterior probability.
