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Information, Physics, and Computation (Oxford Graduate Texts): Mézard, Marc, Montanari, Andrea: 8601410201722: Amazon.com: Books
amazon.com·1d
📐Compression Mathematics
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Keeping Probabilities Honest: The Jacobian Adjustment
towardsdatascience.com·2d
🎯Arithmetic Coding Theory
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Performance Hints for BigQuery
trmlabs.com·4h·
Discuss: Hacker News
🚀Query Optimization
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Treating Functions as Vectors in Hilbert Space
hackaday.com·1d
📐Linear Algebra
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Gaussian concentration bounds for probabilistic cellular automata | Journal of Statistical Physics
link.springer.com·1d
🔲Cellular Automata
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Opening the Black Box of Deep Neural Networks via Information
paperium.net·1d·
Discuss: DEV
🧠Machine Learning
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From Zero to QED: An informal introduction to formality in Lean 4
sdiehl.github.io·1d
🔬Lean
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What Deep Learning Theory Teaches Us About AI Memory
dev.to·1d·
Discuss: DEV
🧠Learned Compression
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Natural language processing for word sense disambiguation and information extraction
arxiv.org·15h·
Discuss: r/compsci
📥Feed Aggregation
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Streaming compression beats framed compression
bou.ke·2d·
Discuss: Hacker News
🌐WebSocket Framing
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Book Review: Why Machines Learn
philippdubach.com·1d·
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🧠Machine Learning
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Does the QUIC handshake require compression to be fast?
fastly.com·1d·
Discuss: Hacker News
🌐DNS over QUIC
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Courses with certificates
codefinity.com·17h
🧠Neural Codecs
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Benchmarking and Enhancing VLM for Compressed Image Understanding
arxiv.org·2d
🧠Learned Compression
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What I Learned Building a Storage Engine That Outperforms RocksDB
tidesdb.com·1h·
Discuss: Hacker News, r/programming
🦀Rusty Databases
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Stanford CS 224N | Natural Language Processing with Deep Learning
web.stanford.edu·1d
🧠Machine Learning
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Optimizing Bracha's Reliable Broadcast: Shaving Rounds off a 37-Year-Old Algorithm
blog.can.ac·3d
🤝Paxos Consensus
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PhD Thesis An INFORMATION THEORETIC APPROACH TO THE EXPRESSIVENESS OF PROGRAMMING LANGUAGES by Joseph Ray Davidson July 2015
macs.hw.ac.uk·3d
💻Programming languages
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Pythonic Best Practices & Idioms
dev.to·17h·
Discuss: DEV
📝Concrete Syntax
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wwes4/AI_Accel_1.5x: AI acceleration framework for ~1.5x speedups in mid-sized models via tension-based pruning. Built utilizing xAI's Grok.
github.com·1d·
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📊Quantization
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