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.

168,695 papers · 148 categories

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4 results for “correct-by-construction”

Safe Predictors for Enforcing Input-Output Specificationscs.LG

Safe neural networks for input-output specifications.

problem Ensuring machine learning models adhere to input-output constraints.

method Designing constrained predictors and combining them safely.

result Demonstrated on synthetic and real-world datasets.

machine learning neural networks input-output constraints correct-by-construction convex combination

2020-01-29abs ↗pdf ↗

dtControl: Decision Tree Learning Algorithms for Controller Representationcs.LG

dtControl uses decision trees to represent controllers efficiently and explainably.

problem Representing controllers concisely and explainably.

method dtControl uses decision tree learning algorithms to represent controllers. Novel techniques for determinizing controllers are introduced.

result Novel techniques for determinizing controllers during decision tree construction are extremely efficient, yielding small decision trees.

decision trees controllers correct-by-construction linear binary classifiers determinization

2020-02-12abs ↗pdf ↗

Learning Proposals for Probabilistic Programs with Inference Combinatorsstat.ML

Develops inference combinators for probabilistic programs using neural networks.

problem Creating efficient proposals for probabilistic program inference.

method Inference combinators using neural network parameterization of proposals.

result Correct by construction variational methods tailored to specific models.

probabilistic programming inference combinators neural networks variational methods amortized Gibbs sampling

2021-03-01abs ↗pdf ↗

EKM: An exact, polynomial-time algorithm for the

K

-medoids problemcs.LG

EKM solves the K-medoids problem in polynomial time.

problem The

K

-medoids problem in data analysis.

method EKM is a novel algorithm using transformational programming and combinatorial generation.

result EKM solves the

K

-medoids problem in worst-case $O\left(N^{K+1} ight)$ time complexity.

K-medoids clustering polynomial time exact algorithm data analysis

2024-05-16abs ↗pdf ↗