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← Optimization & Theory
Deep Learning
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Optimization & Theory
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Theory
1072 directly classified papers
Papers per year
2007: 1
2010: 4
2011: 1
2012: 3
2013: 4
2014: 5
2015: 2
2016: 11
2017: 31
2018: 47
2019: 67
2020: 97
2021: 128
2022: 225
2023: 155
2024: 209
2025: 81
2026: 1
Papers
Understanding the Loss Surface of Neural Networks for Binary Classification
ICML 2018
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
ICML 2018
Convergence guarantees for a class of non-convex and non-smooth optimization problems
ICML 2018
Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima
ICML 2018
Stability and Generalization of Learning Algorithms that Converge to Global Optima
ICML 2018
Stronger Generalization Bounds for Deep Nets via a Compression Approach
ICML 2018
Spectral Filtering for General Linear Dynamical Systems
NIPS 2018
Blind Deconvolutional Phase Retrieval via Convex Programming
NIPS 2018
Modern Neural Networks Generalize on Small Data Sets
NIPS 2018
How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective
NIPS 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
NIPS 2018
Scaling provable adversarial defenses
NIPS 2018
Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks
NIPS 2018
Structured Local Minima in Sparse Blind Deconvolution
NIPS 2018
Are ResNets Provably Better than Linear Predictors?
NIPS 2018
DeepPINK: reproducible feature selection in deep neural networks
NIPS 2018
Efficient Formal Safety Analysis of Neural Networks
NIPS 2018
Fast generalization error bound of deep learning from a kernel perspective
AISTATS 2018
Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation
AISTATS 2018
The emergence of spectral universality in deep networks
AISTATS 2018
Information-based Adaptive Stimulus Selection to Optimize Communication Efficiency in Brain-Computer Interfaces
NIPS 2018
A Biresolution Spectral Framework for Product Quantization
CVPR 2018
An Empirical Evaluation of Sketched SVD and its Application to Leverage Score Ordering
ACML 2018
Gradient Estimation with Simultaneous Perturbation and Compressive Sensing
JMLR 2018
Visualizing the Loss Landscape of Neural Nets
NIPS 2018
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