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Second-order methods

Use second-order statistics to process data.

Papers

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Showing 126–150 of 181 papers

TitleStatusHype
Learning-Augmented Sketches for Hessians—0
LocoProp: Enhancing BackProp via Local Loss Optimization—0
Meta-descent for Online, Continual Prediction—0
Minibatching Offers Improved Generalization Performance for Second Order Optimizers—0
Mirror Prox Algorithm for Large-Scale Cell-Free Massive MIMO Uplink Power Control—0
Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles—0
Nesterov's Acceleration For Approximate Newton—0
Nestrov's Acceleration For Second Order Method—0
Newton methods based convolution neural networks using parallel processing—0
Newton-Stein Method: An optimization method for GLMs via Stein's Lemma—0
Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma—0
On backpropagating Hessians through ODEs—0
Online Second Order Methods for Non-Convex Stochastic Optimizations—0
On the efficiency of Stochastic Quasi-Newton Methods for Deep Learning—0
On the importance of initialization and momentum in deep learning—0
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks—0
Oracle Complexity of Second-Order Methods for Finite-Sum Problems—0
Practical Newton-Type Distributed Learning using Gradient Based Approximations—0
Preconditioners for the Stochastic Training of Neural Fields—0
Provable Regret Bounds for Deep Online Learning and Control—0
Deep Reinforcement Learning via L-BFGS Optimization—0
Fast and Furious Convergence: Stochastic Second Order Methods under InterpolationCode0
Differentially Private Image Classification from FeaturesCode0
Adaptive Consensus Optimization Method for GANsCode0
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic ProgrammingCode0
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