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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.

168,742 papers · 148 categories

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2 results for “logistic-softmax”

Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classificationcs.LG

Revises logistic-softmax likelihood for Bayesian meta-learning in few-shot classification.

problem Inherent uncertainty in logistic-softmax leads to suboptimal performance in meta-learning.

method Redesigns logistic-softmax likelihood with a temperature parameter for better control of prior confidence.

result Achieves well-calibrated uncertainty estimates and comparable/superior performance on benchmark datasets.

Bayesian meta-learning few-shot classification logistic-softmax temperature parameter data augmentation

2023-10-16abs ↗pdf ↗

On Universal Features for High-Dimensional Learning and Inferencecs.LG

The paper identifies universal features for high-dimensional data inference.

problem Identifying universal low-dimensional features from high-dimensional data for inference tasks.

method Introduces natural notions of universality and shows a local equivalence among them, using information geometry.

result Reveals the complementary roles of various data analysis techniques.

high-dimensional data inference universal features information geometry singular value decomposition

2019-11-20abs ↗pdf ↗