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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.

168,695 papers · 148 categories

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1122 · Oct 201719922001200920172026
24 results for Checkers

We present a novel language adaptable spell checking system which detects spelling errors and suggests context sensitive corrections in real-time. We show that our system can be extended to new languages with minimal language-specific processing. Available literature majorly discusses spell checkers for English but the…

2019-10-23abs ↗pdf ↗

We consider triangulations of surfaces with edges painted three colors so that edges of each triangle have different colors. Such structures arise as Belyi data (or Grothendieck dessins d'enfant), on the other hand they enumerate pairs of permutations determined up to a common conjugation. The topic of these notes is l…

2017-10-31abs ↗pdf ↗

This paper reviews the checkered history of predictive distributions in statistics and discusses two developments, one from recent literature and the other new. The first development is bringing predictive distributions into machine learning, whose early development was so deeply influenced by two remarkable groups at …

2017-10-24abs ↗pdf ↗

Efficient verified double auctions improve matching speed and detect errors.

problem Improving the efficiency and reliability of double auctions in financial markets.
method Formally verified implementation using Coq proof assistant, reducing time complexity and improving error detection.
result Improved efficiency with O(nlogn)O(n \log n) time complexity, reducing runtime from days to minutes.

A third of adults in America use the Internet to diagnose medical concerns, and online symptom checkers are increasingly part of this process. These tools are powered by diagnosis models similar to clinical decision support systems, with the primary difference being the coverage of symptoms and diagnoses. To be useful …

2019-12-11abs ↗pdf ↗

Developed a neural topic model for classifying COVID-19 disinformation.

problem Tackles the challenge of disinformation during the COVID-19 pandemic.
method Classification-aware neural topic model (CANTM) for COVID-19 disinformation.
result Demonstrated the effectiveness of CANTM in classifying COVID-19 disinformation.

From the early days of computing, games have been important testbeds for studying how well machines can do sophisticated decision making. In recent years, machine learning has made dramatic advances with artificial agents reaching superhuman performance in challenge domains like Go, Atari, and some variants of poker. A…

2019-02-01abs ↗pdf ↗

A new property fixes look-ahead bias in backtesting and trading pipelines.

problem Fixing look-ahead bias in backtesting and trading pipelines.
method Developed a pipeline calculus separating availability from reference time, and a type-and-effect system for the value-independent fragment.
result The check scales linearly and catches all leaks, including those missed by differential and tiling detectors.

Three training methods for language models are shown to be variations of one another.

problem Training language models to reason effectively using different methods.
method Three training methods: GRPO, Dr. GRPO, and DAPO.
result All three methods adjust a single number: standard deviation, measuring disagreement in answers.

PEREGRiNN verifies safety of ReLU NNs by penalizing relaxation in a greedy manner.

problem Formal verification of safety specifications for ReLU NNs.
method Uses a relaxed convex program to verify polytopic input/output constraints, penalizing relaxation and forcing largest relaxations to early layers.
result Significantly faster and more properties verified compared to other approaches.