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⛰️ Gradient Descent
Optimization, Learning Rate, Backpropagation, Convergence
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185617
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Gradient
Descent
For
Logistic
and Linear Regression
🎪
Convex Optimization
medium.com
·
5d
Convergence rates for gradient descent in the training of
overparameterized
artificial neural networks with
piecewise
affine activation
🎪
Convex Optimization
arxiv.org
·
20h
LoRA
and Weight
Decay
(2023)
🎪
Convex Optimization
irhum.github.io
·
2d
·
Hacker News
Streamlined
optical training of large-scale modern deep learning
architectures
with direct feedback alignment
🗺️
UMAP
pnas.org
·
1d
Backpropagation
🎪
Convex Optimization
pugsley.bearblog.dev
·
3d
Convergent
Abstraction
Hypothesis
🔢
Embeddings
lesswrong.com
·
6d
MANGO
: Meta-Adaptive Network Gradient Optimization for Online
Continual
Learning
🎪
Convex Optimization
arxiv.org
·
20h
Training Neural Networks with
Optimal
Double-Bayesian
Learning
📊
Empirical Bayes
arxiv.org
·
20h
Can Adaptive Gradient Methods Converge under
Heavy-Tailed
Noise? A Case Study of
AdaGrad
🎪
Convex Optimization
arxiv.org
·
1d
Fast Spawn\&
Prune
(FS\&P): Global convergence of stochastic
conic
particle gradient descent via birth/death process
🎪
Convex Optimization
arxiv.org
·
20h
High-dimensional Limit of
SGD
for
Diagonal
Linear Networks
🗺️
Manifold Learning
arxiv.org
·
1d
Replacement Learning: Training Neural Networks with
Fewer
Parameters
🗺️
Manifold Learning
arxiv.org
·
20h
Feature Learning in
Linear-Width
Two-Layer Networks: Two vs. One Step of Gradient
Descent
📊
Empirical Bayes
arxiv.org
·
1d
LionMuon
:
Alternating
Spectral and Sign Descent for Efficient Training
🗺️
Manifold Learning
arxiv.org
·
20h
Optimal
Asymptotic
Rates for (Stochastic) Gradient
Descent
under the Local PL-Condition: A Geometric Approach
🎪
Convex Optimization
arxiv.org
·
5d
Self-supervised
local learning rules learn the hidden
hierarchical
structure of high-dimensional data
📊
Empirical Bayes
arxiv.org
·
1d
Hybrid-LoRA
:
Bridging
Full Fine-Tuning and Low-Rank Adaptation for Post-Training
🗺️
UMAP
arxiv.org
·
20h
Rethinking
Neural Network Learning Rates: A
Stackelberg
Perspective
📊
Empirical Bayes
arxiv.org
·
2d
Optimized
projection-free
algorithms for online learning: construction and worst-case analysis
🎪
Convex Optimization
arxiv.org
·
20h
Turning
Stale
Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight
Zeroth-Order
Optimization
🎪
Convex Optimization
arxiv.org
·
5d
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