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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,181 papers · 148 categories

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1 result for “Multi-Focus”

Multi-focus Attention Network for Efficient Deep Reinforcement Learningcs.LG

Proposes MANet for efficient DRL with less experience samples.

problem Inefficient DRL due to lack of spatial abstraction and attention.

method Divides input into partial states, parallel attention layers attend to relevant partial states, estimates state-action values.

result Significantly less experience samples for high performance.

Deep Reinforcement Learning Attention Networks Efficient Learning Multi-Focus Partial States

2017-12-13abs ↗pdf ↗