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🎮 Reinforcement Learning
Q-Learning, Policy Gradients, Environments, Rewards
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123650
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930.4
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Nonparametric
Bayesian Optimization for General
Rewards
arxiv.org
·
1d
⚡
Query Optimization
Learning in Context, Guided by Choice: A Reward-Free
Paradigm
for Reinforcement Learning with
Transformers
arxiv.org
·
1d
🔀
Transformers
Ai’s ‘
steering
’ Made Far More
Precise
With New Fine-Tuning Technique
quantumzeitgeist.com
·
1d
🔀
Transformers
Variable
Rewards Produce
Dopamine
artlu.bearblog.dev
·
1d
🤖
AI
A blockchain-enhanced
evolutionary
game model for multi-agent collaboration in the
photovoltaic
industry chain
sciencedirect.com
·
3h
🌐
Distributed Systems
Show HN:
ContinualCode
– a coding agent that updates its
weights
from feedback
sdan.github.io
·
1d
·
Discuss:
Hacker News
🔀
Transformers
The Machine Learning
Practitioner
’s Guide to
Speculative
Decoding
machinelearningmastery.com
·
6h
🔀
Transformers
Beyond the
Hype
: Why Machine Learning is the Strategic
Backbone
of Modern AI
pub.towardsai.net
·
21h
🤖
AI
Decision-Based Artificial Intelligence and the Strategic
Reordering
of Military Power
inss.ndu.edu
·
1d
🤖
AI
Observe
emergent
behavior in autonomous multi-agent LLM networks
agents.glide2.app
·
1d
·
Discuss:
Hacker News
🤖
AI
#2 - Going to second
base
: know your
boundaries
dev.to
·
23h
·
Discuss:
DEV
🤖
AI
Safety
mechanisms
of AI models more
fragile
than expected
techzine.eu
·
1d
🔀
Transformers
Ascend
the Cognitive
Hierarchy
—Don't Waste Time in the Data Layer
realcleardefense.com
·
4h
🔀
Transformers
ArXiv
Endorsement
for Paper on Neuro-Symbolic Architecture for Financial Agents
news.ycombinator.com
·
3h
·
Discuss:
Hacker News
🔀
Transformers
🥇Top AI
Papers
of the Week
nlp.elvissaravia.com
·
3d
🤖
AI
Pushing
Deeper
Into AI Music Creation With
Mozart
AI
forbes.com
·
5h
🤖
AI
Becoming
More
blog.startifact.com
·
17h
🤖
AI
When the Matrix Breaks: Failure
Modes
of Early
Matching
Systems
linkedin.com
·
2h
·
Discuss:
DEV
🌐
Distributed Systems
Information-Theoretic
Derivation
of Energy, Speed Bounds, and Quantum Theory
link.aps.org
·
3h
🌐
Distributed Systems
Reply to
Cecchi
and
Palminteri
: On the need to model temporal variation in learning rates
pnas.org
·
4h
🔀
Transformers
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