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Optimization

14,983 papers

Papers per year

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Papers

Coresets for Classification – Simplified and Strengthened NIPS 2021
Overlapping Spaces for Compact Graph Representations NIPS 2021
Sparse Spiking Gradient Descent NIPS 2021
A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast NIPS 2021
Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence NIPS 2021
Sifting through the noise: Universal first-order methods for stochastic variational inequalities NIPS 2021
Demystifying and Generalizing BinaryConnect NIPS 2021
CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator NIPS 2021
Towards Stable and Robust AdderNets NIPS 2021
Alignment Attention by Matching Key and Query Distributions NIPS 2021
Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations NIPS 2021
Nonsmooth Implicit Differentiation for Machine-Learning and Optimization NIPS 2021
A novel notion of barycenter for probability distributions based on optimal weak mass transport NIPS 2021
Revisiting Smoothed Online Learning NIPS 2021
Provably Faster Algorithms for Bilevel Optimization NIPS 2021
A Continuous Mapping For Augmentation Design NIPS 2021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression NIPS 2021
Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers NIPS 2021
Exponential Graph is Provably Efficient for Decentralized Deep Training NIPS 2021
Learning Treatment Effects in Panels with General Intervention Patterns NIPS 2021
Convergence of adaptive algorithms for constrained weakly convex optimization NIPS 2021
On the Convergence of Step Decay Step-Size for Stochastic Optimization NIPS 2021
Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems NIPS 2021
Fair Clustering Under a Bounded Cost NIPS 2021
Rethinking the Variational Interpretation of Accelerated Optimization Methods NIPS 2021