Information Must Flow: Recursive Bootstrapping for Information Bottleneck in Optimal Transport
arxiv.org·1d
🧠Machine Learning
Categorical Features: The Backbone of Search & Recs Engineering
shaped.ai·1d
🧠Learned Indexing
COLI: A Hierarchical Efficient Compressor for Large Images
arxiv.org·6h
🧠Neural Compression
Translation using deep neural networks – Transformer
aamster.github.io·1d·
Discuss: Hacker News
🧠Neural Codecs
On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization
arxiv.org·1d
🧠Machine Learning
Incomplete Multiview Learning via Wyner Common Information
arxiv.org·1d
📊Learned Metrics
Learning to Quantize and Precode in Massive MIMO Systems for Energy Reduction: a Graph Neural Network Approach
arxiv.org·6h
📊Quantization
Class-Proportional Coreset Selection for Difficulty-Separable Data
arxiv.org·6h
🧠Machine Learning
🎯 Building Attention Mechanisms from Scratch: A Complete Guide to Understanding Transformers
dev.to·2d·
Discuss: DEV
📊Learned Metrics
Evaluating Image Compression Tools
rachelplusplus.me.uk·3d·
Discuss: Hacker News
📊Rate-Distortion Theory
Robust-Multi-Task Gradient Boosting
arxiv.org·6h
📊Learned Metrics
Spatial Lifting for Dense Prediction
arxiv.org·1d
🧠Machine Learning
Graph Convolutional Branch and Bound
arxiv.org·2d
🧮Vector Embeddings
A Minimal DDPM
github.com·8h·
Discuss: Hacker News
🧠Machine Learning
AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air
arxiv.org·6h
💻Local LLMs
Energy Efficiency in AI for 5G and Beyond: A DeepRx Case Study
arxiv.org·1d
🧠Machine Learning
Context-Aware Regularization with Markovian Integration for Attention-Based Nucleotide Analysis
arxiv.org·1d
🧠Machine Learning
Compressed data structures for Heegaard splittings
arxiv.org·6h
🕳️Persistent Homology
A Neural Network Model of Complementary Learning Systems: Pattern Separation and Completion for Continual Learning
arxiv.org·6h
🧠Neural Compression
Balancing Semantic Relevance and Engagement in Related Video Recommendations
arxiv.org·1d
🔍Information Retrieval