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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)

Pruning Filter in Filter NIPS 2020
Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization NIPS 2020
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search NIPS 2020
BERT Loses Patience: Fast and Robust Inference with Early Exit NIPS 2020
Batch normalization provably avoids ranks collapse for randomly initialised deep networks NIPS 2020
What if Neural Networks had SVDs? NIPS 2020
HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks NIPS 2020
Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features model NIPS 2020
Collegial Ensembles NIPS 2020
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks NIPS 2020
MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles NIPS 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching NIPS 2020
Semialgebraic Optimization for Lipschitz Constants of ReLU Networks NIPS 2020
Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics NIPS 2020
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search AAAI 2020
Understanding and Improving Proximity Graph Based Maximum Inner Product Search AAAI 2020
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods AAAI 2020
Robust Low-Rank Discovery of Data-Driven Partial Differential Equations AAAI 2020
HDK: Toward High-Performance Deep-Learning-Based Kirchhoff Analysis AAAI 2020
A Deep Neural Network Model of Particle Thermal Radiation in Packed Bed AAAI 2020
Shoreline: Data-Driven Threshold Estimation of Online Reserves of Cryptocurrency Trading Platforms AAAI 2020
Deep Reservoir Computing Meets 5G MIMO-OFDM Systems in Symbol Detection AAAI 2020
SPAN: A Stochastic Projected Approximate Newton Method AAAI 2020
An Effective Hard Thresholding Method Based on Stochastic Variance Reduction for Nonconvex Sparse Learning AAAI 2020
Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks AAAI 2020