6,328 results for distribut · 0.261s

arxiv.org/abs/2309.14127v1

Dual digraphs of finite meet-distributive and modular lattices

We describe the digraphs that are dual representations of finite lattices satisfying conditions related to meet-distributivity and modularity. This is done using the dual digraph representation of finite lattices by Craig, Gouveia and Haviar (2015)....

arxiv.org/abs/2310.17392v3

The Power of Simple Menus in Robust Selling Mechanisms

We study a robust selling problem where a seller attempts to sell one item to a buyer but is uncertain about the buyer's valuation distribution. Existing literature shows that robust screening provides a stronger theoretical guarantee than robust det...

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arxiv.org/abs/1311.5966v2

Optimal mechanisms with simple menus

We consider optimal mechanism design for the case with one buyer and two items. The buyer's valuations towards the two items are independent and additive. In this setting, optimal mechanism is unknown for general valuation distributions. We obtain tw...

github.com/elastic/elasticsearch

elastic/elasticsearch

Free and Open Source, Distributed, RESTful Search Engine (⭐ 76287)

arxiv.org/abs/2104.08203v1

Why Machine Learning Integrated Patient Flow Simulation?

Patient flow analysis can be studied from a clinical and or operational perspective using simulation. Traditional statistical methods such as stochastic distribution methods have been used to construct patient flow simulation submodels such as patien...

arxiv.org/abs/1705.00677v1

A Distributed Method for Optimal Capacity Reservation

We consider the problem of reserving link capacity in a network in such a way that any of a given set of flow scenarios can be supported. In the optimal capacity reservation problem, we choose the reserved link capacities to minimize the reservation...

arxiv.org/abs/2510.03798v1

Robust Batched Bandits

The batched multi-armed bandit (MAB) problem, in which rewards are collected in batches, is crucial for applications such as clinical trials. Existing research predominantly assumes light-tailed reward distributions, yet many real-world scenarios, in...

arxiv.org/abs/2007.10928v1

What is important about the No Free Lunch theorems?

The No Free Lunch theorems prove that under a uniform distribution over induction problems (search problems or learning problems), all induction algorithms perform equally. As I discuss in this chapter, the importance of the theorems arises by using...

arxiv.org/abs/2404.09629v1

Quantifying fair income distribution in Thailand

Given a vast concern about high income inequality in Thailand as opposed to empirical findings around the world showing people's preference for fair income inequality over unfair income equality, it is therefore important to examine whether inequalit...

arxiv.org/abs/2412.04727v1

Learning to Translate Noise for Robust Image Denoising

Deep learning-based image denoising techniques often struggle with poor generalization performance to out-of-distribution real-world noise. To tackle this challenge, we propose a novel noise translation framework that performs denoising on an image w...

arxiv.org/abs/2002.10450v5

Effective forms of the Sato--Tate conjecture

We prove effective forms of the Sato-Tate conjecture for holomorphic cuspidal newforms which improve on the author's previous work (solo and joint with Lemke Oliver). We also prove an effective form of the joint Sato-Tate distribution for two twist-i...

arxiv.org/abs/1109.3295v2

Microlensing Binaries Discovered through High-Magnification Channel

Microlensing can provide a useful tool to probe binary distributions down to low-mass limits of binary companions. In this paper, we analyze the light curves of 8 binary lensing events detected through the channel of high-magnification events during...