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🧠 Machine Learning

Information Theory, Compression Bounds, Feature Learning, Neural Networks

Categorical Features: The Backbone of Search & Recs Engineering
shaped.ai·2d
🧠Learned Indexing
Spatial Lifting for Dense Prediction
arxiv.org·1d
🌀Riemannian Computing
Canonical Bayesian Linear System Identification
arxiv.org·23h
📊Quantization
Over 30 AI models have been trained at 10^25 FLOP or greater
epoch.ai·12h·
Discuss: Hacker News
⚡Performance Mythology
The Power of Certainty: How Confident Models Lead to Better Segmentation
arxiv.org·1d
📊Quantization
Contrastive-KAN: A Semi-Supervised Intrusion Detection Framework for Cybersecurity with scarce Labeled Data
arxiv.org·23h
🎯Threat Hunting
Class-Proportional Coreset Selection for Difficulty-Separable Data
arxiv.org·23h
🧮Kolmogorov Complexity
MediaMind AI - Intelligent Content Discovery Platform with Algolia MCP Server
dev.to·12h·
Discuss: DEV
🧭Content Discovery
A Neural Network Model of Complementary Learning Systems: Pattern Separation and Completion for Continual Learning
arxiv.org·23h
🧠Neural Compression
Contrastive Language-Image Pre-Training Model based Semantic Communication Performance Optimization
arxiv.org·1d
🧠Neural Codecs
Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting
arxiv.org·1d
📈Time Series
Robust-Multi-Task Gradient Boosting
arxiv.org·23h
📊Learned Metrics
A parametric activation function based on Wendland RBF
arxiv.org·23h
📊Quantization
What are Vectors and Matrices?
dev.to·2d·
Discuss: DEV
📐Linear Algebra
Become a machine learning engineer in five to seven steps
maxmynter.com·13h·
Discuss: Hacker News
🎵Audio ML
Compressed data structures for Heegaard splittings
arxiv.org·23h
🕳️Persistent Homology
Incomplete Multiview Learning via Wyner Common Information
arxiv.org·1d
⧗Information Bottleneck
FedGSCA: Medical Federated Learning with Global Sample Selector and Client Adaptive Adjuster under Label Noise
arxiv.org·23h
🌀Differential Geometry
The Bayesian Approach to Continual Learning: An Overview
arxiv.org·1d
🎛️Feed Filtering
Energy Efficiency in AI for 5G and Beyond: A DeepRx Case Study
arxiv.org·1d
⧗Information Bottleneck
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