conftrace_
← Deep Learning
Deep Learning ›

Optimization & Theory

6,829 papers (27 classified directly here)

Subtopics

Model Compression (1,785) Optimization (1,664) Efficient Computing (1,579) Theory (1,082) Neural Network Optimization (903) Evaluation (509) Loss Functions (123) Interpretability (105) Stochastic Methods (97) Regularization (77) Generalization (24) Sparse Optimization (7)

Papers per year

8
50
642
1173
'10
'15
'20
'25

Papers (including subtopics)

P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification CVPR 2019
DeepView: View Synthesis With Learned Gradient Descent CVPR 2019
Inverse Path Tracing for Joint Material and Lighting Estimation CVPR 2019
Structured Knowledge Distillation for Semantic Segmentation CVPR 2019
Understanding the Disharmony Between Dropout and Batch Normalization by Variance Shift CVPR 2019
Circulant Binary Convolutional Networks: Enhancing the Performance of 1-Bit DCNNs With Circulant Back Propagation CVPR 2019
Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks CVPR 2019
Learning to Sample CVPR 2019
Variational Convolutional Neural Network Pruning CVPR 2019
Towards Optimal Structured CNN Pruning via Generative Adversarial Learning CVPR 2019
Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression CVPR 2019
Fully Quantized Network for Object Detection CVPR 2019
MnasNet: Platform-Aware Neural Architecture Search for Mobile CVPR 2019
Snapshot Distillation: Teacher-Student Optimization in One Generation CVPR 2019
Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation CVPR 2019
Spectral Metric for Dataset Complexity Assessment CVPR 2019
MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation CVPR 2019
Deep Rigid Instance Scene Flow CVPR 2019
Robust Video Stabilization by Optimization in CNN Weight Space CVPR 2019
Compressing Convolutional Neural Networks via Factorized Convolutional Filters CVPR 2019
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses CVPR 2019
A General and Adaptive Robust Loss Function CVPR 2019
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration CVPR 2019
Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss CVPR 2019
Parallel Optimal Transport GAN CVPR 2019