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)

Learning Student Networks with Few Data AAAI 2020
URNet: User-Resizable Residual Networks with Conditional Gating Module AAAI 2020
Understanding the Disharmony between Weight Normalization Family and Weight Decay AAAI 2020
On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks AAAI 2020
RTN: Reparameterized Ternary Network AAAI 2020
Learning to Auto Weight: Entirely Data-Driven and Highly Efficient Weighting Framework AAAI 2020
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates AAAI 2020
Stochastic Loss Function AAAI 2020
An ADMM Based Framework for AutoML Pipeline Configuration AAAI 2020
Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio AAAI 2020
Fastened CROWN: Tightened Neural Network Robustness Certificates AAAI 2020
Inefficiency of K-FAC for Large Batch Size Training AAAI 2020
The HSIC Bottleneck: Deep Learning without Back-Propagation AAAI 2020
PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices AAAI 2020
Neural Inheritance Relation Guided One-Shot Layer Assignment Search AAAI 2020
Improved Knowledge Distillation via Teacher Assistant AAAI 2020
Radial and Directional Posteriors for Bayesian Deep Learning AAAI 2020
Stochastic Approximate Gradient Descent via the Langevin Algorithm AAAI 2020
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains AAAI 2020
DARB: A Density-Adaptive Regular-Block Pruning for Deep Neural Networks AAAI 2020
Linear Context Transform Block AAAI 2020
Empirical Bounds on Linear Regions of Deep Rectifier Networks AAAI 2020
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference AAAI 2020
Deep Time-Stream Framework for Click-through Rate Prediction by Tracking Interest Evolution AAAI 2020
HLHLp: Quantized Neural Networks Training for Reaching Flat Minima in Loss Surface AAAI 2020