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🎪 Convex Optimization
Gradient Methods, Duality, Convex Sets, Global Minima
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121389
posts in
2.41
s
On
semidefinite-representable
sets over valued fields
arxiv.org
·
1d
📐
Matrix Factorization
Convex
Dominance
in Deep Learning I: A Scaling Law of Loss and Learning Rate
arxiv.org
·
2d
⛰️
Gradient Descent
An uncertainty aware transformer framework for wind power
forecasting
with
multiscale
attention and adaptive feature fusion
chipublib.idm.oclc.org
·
1d
📐
Matrix Factorization
LLM Performance in
Astro
, React,
Tailwind
and Cloudflare
10xbench.ai
·
1d
·
Discuss:
Hacker News
🚀
Streamlit
Tutorial – What is a
variational
autoencoder
?
jaan.io
·
2d
·
Discuss:
Hacker News
⛰️
Gradient Descent
Recursive
self-improvement
from AI models
marginalrevolution.com
·
1d
·
Discuss:
Hacker News
⛰️
Gradient Descent
An automated geometric space
curve
approach for designing dynamically
corrected
gates
nature.com
·
1d
🔗
Markov Chains
Beyond
Kuramoto
Models: Associative Memory and Plastic
Synapses
in ML Ensembles
hackernoon.com
·
18h
⛰️
Gradient Descent
A multi-agent reinforcement learning approach to autonomous aircraft
taxiing
with
taxiing
time, fuel consumption, and
emission
optimization
sciencedirect.com
·
19h
⛰️
Gradient Descent
Image
Classification
with
Convolutional
Neural Networks
dev.to
·
2d
·
Discuss:
DEV
🗺️
UMAP
strangehospital/Frontier-Dynamics-Project
: On-Demand A.I
Computation
github.com
·
1d
·
Discuss:
Hacker News
⛰️
Gradient Descent
A 3D pocket-aware and
evolutionary
conserved
interaction guided diffusion model for molecular optimization
sonomarpa.sonoma.lib.ca.us
·
1d
📐
Computational Geometry
Drifting
models
breno.bearblog.dev
·
2d
⛰️
Gradient Descent
Wake model-free active power control for wind-storage coordination using a
state-decoupled
MATD3
algorithm
sciencedirect.com
·
19h
⛰️
Gradient Descent
SAE Feature
Matchmaking
(Layer-to-Layer) by
Mitali
M
greaterwrong.com
·
2d
📐
Matrix Factorization
JRFM
, Vol. 19,
Pages
132: A Hybrid Framework for Multi-Stock Trading: Deep Q-Networks with Portfolio...
mdpi.com
·
2d
⛰️
Gradient Descent
The Role of Signal To
Noise
in Loss
Convergence
pub.towardsai.net
·
1d
⛰️
Gradient Descent
Observability
inequalities
for heat equations with
potentials
chipublib.idm.oclc.org
·
17h
🎲
Stochastic differential equation
Lean
4 and the Curry–Howard
correspondence
wildonblog.wordpress.com
·
2d
🔗
Markov Chains
Learning Coupled Actions of Lie Groups:
Kuramoto
Models for Robotics and
Hyperbolic
Data
hackernoon.com
·
2d
🗺️
Manifold Learning
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