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← Optimization & Theory
Machine Learning
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Optimization & Theory
›
Neural Network Optimization
3,648 papers
Papers per year
2001: 1
2003: 1
2005: 2
2006: 3
2007: 6
2008: 1
2009: 7
2010: 5
2011: 7
2012: 9
2013: 17
2014: 18
2015: 40
2016: 76
2017: 113
2018: 214
2019: 324
2020: 414
2021: 489
2022: 445
2023: 524
2024: 469
2025: 386
2026: 77
Papers
A Variant of Anderson Mixing with Minimal Memory Size
NIPS 2022
Invertible Monotone Operators for Normalizing Flows
NIPS 2022
The Curse of Unrolling: Rate of Differentiating Through Optimization
NIPS 2022
On the non-universality of deep learning: quantifying the cost of symmetry
NIPS 2022
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference
NIPS 2022
Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators
NIPS 2022
The Role of Baselines in Policy Gradient Optimization
NIPS 2022
SAPipe: Staleness-Aware Pipeline for Data Parallel DNN Training
NIPS 2022
Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits
NIPS 2022
Large-batch Optimization for Dense Visual Predictions: Training Faster R-CNN in 4.2 Minutes
NIPS 2022
Most Activation Functions Can Win the Lottery Without Excessive Depth
NIPS 2022
Towards Theoretically Inspired Neural Initialization Optimization
NIPS 2022
Theoretically Provable Spiking Neural Networks
NIPS 2022
Understanding Deep Contrastive Learning via Coordinate-wise Optimization
NIPS 2022
Surprising Instabilities in Training Deep Networks and a Theoretical Analysis
NIPS 2022
Finite-Time Analysis of Adaptive Temporal Difference Learning with Deep Neural Networks
NIPS 2022
Benign Underfitting of Stochastic Gradient Descent
NIPS 2022
Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
NIPS 2022
Instability and Local Minima in GAN Training with Kernel Discriminators
NIPS 2022
Optimal and Adaptive Monteiro-Svaiter Acceleration
NIPS 2022
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit
NIPS 2022
An In-depth Study of Stochastic Backpropagation
NIPS 2022
To update or not to update? Neurons at equilibrium in deep models
NIPS 2022
A Combinatorial Perspective on the Optimization of Shallow ReLU Networks
NIPS 2022
On-Device Training Under 256KB Memory
NIPS 2022
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