On-device research index

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.

169,236 papers · 148 categories

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7 results for “point-weighting”

Unsupervised Hypergraph Feature Selection via a Novel Point-Weighting Framework and Low-Rank Representationcs.LG

Proposes a novel feature selection method for hypergraphs.

problem The 'curse of dimensionality' problem in feature selection.

method Unsupervised hypergraph feature selection via point-weighting and low-rank representation.

result Significant improvement over state-of-the-art feature selection methods.

feature selection hypergraph unsupervised learning low-rank representation point-weighting

2018-08-25abs ↗pdf ↗

Calabi-Yau metrics with conical singularities along line arrangementsmath.DG

New metrics found with cone singularities along line arrangements.

problem Existence of Calabi-Yau metrics with conical singularities.

method Ricci-flat Kähler metric with cone singularities along weighted line arrangements.

result Existence of a Ricci-flat Kähler metric with cone singularities.

Calabi-Yau metrics conical singularities line arrangements Ricci-flat Kähler

2017-12-21abs ↗pdf ↗

Kosniowski's conjecture and weightsmath.DG

The paper confirms a conjecture about compact unitary manifolds with non-empty fixed points.

problem Bounding the dimension of compact unitary manifolds with non-empty fixed points.

method The approach involves confirming Kosniowski's conjecture for almost complex manifolds under specific weight conditions.

result The conjecture is confirmed for manifolds with specific types of weights.

Kosniowski conjecture compact unitary manifolds fixed points weights almost complex manifolds

2018-12-29abs ↗pdf ↗

On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networkscs.LG

Quantized BNNs maintain uncertainty estimation quality despite reduced precision.

problem Reduced precision in BNNs due to quantization.

method Quantized BNNs with 32-bit weights and activations compressed to 16-bit integers.

result Uniform quantization does not significantly degrade uncertainty estimation quality.

Bayesian neural networks quantization uncertainty estimation autonomous driving healthcare

2021-02-22abs ↗pdf ↗

Up or Down? Adaptive Rounding for Post-Training Quantizationcs.LG

AdaRound improves post-training quantization of neural networks.

problem Improving the accuracy of quantized weights in neural networks.

method Adaptive rounding mechanism that adapts to data and task loss.

result AdaRound outperforms rounding-to-nearest and achieves state-of-the-art performance.

quantization post-training adaptive rounding neural networks accuracy

2020-04-22abs ↗pdf ↗

Approximation of Optimal Transport problems with marginal moments constraintsmath.PR

This work relaxes OT problems with marginal moments constraints, achieving finite discrete measures.

problem Solving Optimal Transport problems with marginal moments constraints.

method Relaxation of OT problems using moment constraints and Tchakaloff's theorem.

result The Moment Constrained Optimal Transport problem (MCOT) is achieved by a finite discrete measure.

Optimal Transport Marginal Moments Finite Discrete Measure Tchakaloff's Theorem Convergence Rates

2019-05-14abs ↗pdf ↗

Surprisal Driven

k

-NN for Robust and Interpretable Nonparametric Learningcs.LG

A new $k$ -NN algorithm using surprisal for robust and interpretable nonparametric learning.

problem Complex patterns and relationships in data without strong distribution assumptions.

method Surprisal-driven

k

-NN framework for classification, regression, density estimation, and anomaly detection.

result State-of-the-art results in classification and anomaly detection, competitive regression results.

k-NN surprisal nonparametric learning information theory robustness

2023-11-17abs ↗pdf ↗