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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.

168,657 papers · 148 categories

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6 results for “data-oblivious”

A Separation Result Between Data-oblivious and Data-aware Poisoning Attackscs.LG

New study shows data-oblivious attacks can outperform data-aware ones.

problem Comparing effectiveness of data-oblivious and data-aware poisoning attacks.

method Theoretical study of feature selection with LASSO, focusing on separation between full-information and oblivious attackers.

result Data-oblivious attacks can achieve the same results as full-information attacks for feature selection with LASSO.

poisoning attacks machine learning feature selection LASSO data-oblivious

2020-03-26abs ↗pdf ↗

Oblivious sketching for logistic regressioncs.DS

A new data-oblivious sketch for logistic regression reduces data size while maintaining approximation accuracy.

problem Efficiently solving logistic regression in one pass over a data stream.

method Data-oblivious sketching approach that reduces data size to poly(μdlog n) weighted points.

result Sketching reduces data size significantly and provides approximation guarantees.

logistic regression data stream approximation sketching one pass

2021-07-14abs ↗pdf ↗

Learning Space Partitions for Nearest Neighbor Searchcs.LG

Space partitions of $\mathbb{R}^d$ underlie a vast and important class of fast nearest neighbor search (NNS) algorithms. Inspired by recent theoretical work on NNS for general metric spaces [Andoni, Naor, Nikolov, Razenshteyn, Waingarten STOC 2018, FOCS 2018], we develop a new framework for building space partitions re…

2019-01-24abs ↗pdf ↗

Asymmetric Random Projectionscs.LG

Random projections (RP) are a popular tool for reducing dimensionality while preserving local geometry. In many applications the data set to be projected is given to us in advance, yet the current RP techniques do not make use of information about the data. In this paper, we provide a computationally light way to extra…

2019-06-22abs ↗pdf ↗

DOFEN: Deep Oblivious Forest ENsemblecs.LG

DOFEN improves DNN performance on tabular data benchmarks.

problem DOFEN tackles the performance gap between DNNs and tree-based models on tabular data.

method DOFEN uses a two-level rODT forest ensembling process inspired by oblivious decision trees.

result DOFEN achieves state-of-the-art results on the Tabular Benchmark.

Deep Learning Gradient Boosting Tabular Data Oblivious Decision Trees Ensembling

2024-12-21abs ↗pdf ↗

Sparse sketches with small inversion biascs.DS

A new method reduces the bias in estimating inverse covariance matrices from sketches.

problem Reducing the bias in estimating inverse covariance matrices from sketches.

method Developed a framework for analyzing inversion bias and proposed a new sketching technique called LEverage Score Sparsified (LESS) embeddings.

result The new sketching technique reduces the inversion bias to

O(1/\sqrt d)

for

m=O(d)

, significantly smaller than the

Θ(1)

approximation error.

inversion bias sparse sketches inverse covariance sub-gaussian matrices leverage scores

2020-11-21abs ↗pdf ↗