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Model Architecture

4,351 papers

Papers per year

Papers

Structured Convolutions for Efficient Neural Network Design NIPS 2020
Bayesian Bits: Unifying Quantization and Pruning NIPS 2020
Revisiting Parameter Sharing for Automatic Neural Channel Number Search NIPS 2020
Neural Power Units NIPS 2020
On Correctness of Automatic Differentiation for Non-Differentiable Functions NIPS 2020
Multi-Plane Program Induction with 3D Box Priors NIPS 2020
Towards Learning Convolutions from Scratch NIPS 2020
Theory-Inspired Path-Regularized Differential Network Architecture Search NIPS 2020
Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning NIPS 2020
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning NIPS 2020
Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels NIPS 2020
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures NIPS 2020
Neuron-level Structured Pruning using Polarization Regularizer NIPS 2020
AutoBSS: An Efficient Algorithm for Block Stacking Style Search NIPS 2020
Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point NIPS 2020
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding NIPS 2020
Non-Euclidean Universal Approximation NIPS 2020
TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning NIPS 2020
JAX MD: A Framework for Differentiable Physics NIPS 2020
MCUNet: Tiny Deep Learning on IoT Devices NIPS 2020
Rethinking Importance Weighting for Deep Learning under Distribution Shift NIPS 2020
Neural Architecture Generator Optimization NIPS 2020
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training NIPS 2020
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? NIPS 2020
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks NIPS 2020