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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

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Papers (including subtopics)

Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex AISTATS 2019
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron AISTATS 2019
Adaptive Ensemble Prediction for Deep Neural Networks based on Confidence Level AISTATS 2019
Nonconvex Matrix Factorization from Rank-One Measurements AISTATS 2019
Learning One-hidden-layer ReLU Networks via Gradient Descent AISTATS 2019
Learning One-hidden-layer Neural Networks under General Input Distributions AISTATS 2019
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function AISTATS 2019
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019
On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019
A Fast Sampling Algorithm for Maximum Inner Product Search AISTATS 2019
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019
Fixing Mini-batch Sequences with Hierarchical Robust Partitioning AISTATS 2019
Convergence of Gradient Descent on Separable Data AISTATS 2019
Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization CVPR 2019
Efficient Video Classification Using Fewer Frames CVPR 2019
Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation CVPR 2019
SSN: Learning Sparse Switchable Normalization via SparsestMax CVPR 2019
On Implicit Filter Level Sparsity in Convolutional Neural Networks CVPR 2019
Learning Channel-Wise Interactions for Binary Convolutional Neural Networks CVPR 2019
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack CVPR 2019
Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression CVPR 2019
Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction CVPR 2019
Reflection Removal Using a Dual-Pixel Sensor CVPR 2019
ODE-Inspired Network Design for Single Image Super-Resolution CVPR 2019
Searching for a Robust Neural Architecture in Four GPU Hours CVPR 2019