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Just Sort It! A Simple and Effective Approach to Active Preference Learning

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Sampling-Based AQP in Modern Analytical Engines

Anastasia Ailamaki, Viktor Sanca

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...

ACM2022

Towards a secure and trustworthy imaging with non-fungible tokens

Touradj Ebrahimi, Evgeniy Upenik, Davi Nachtigall Lazzarotto

Non fungible tokens (NFTs) are used to define the ownership of digital assets. More recently, there has been a surge of platforms to auction digital art as well as other digital assets in form of image, video, and audio content of all sorts. Although NFTs ...

2021

The efficiency of stochastic particle schemes for large scale simulations relies on the ability to preserve a uniform distribution of particles in the whole physical domain. While simple particle split and merge algorithms have been considered previously, ...

2019

Device and method for sorting biological entities

Francesco Mondada, Norbert Crot, Frank Bonnet

A device for sorting biological entities is disclosed. The device comprises a channel to canalize the biological entities and a selector having slots to accommodate said entities. Means for detecting and analysing an optical parameter of the biological ent ...

2019

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Sparse recovery from undersampled random quan- tization measurements is a recent active research topic. Previous work asserts that stable recovery can be guaranteed via the basis pursuit dequantizer (BPDQ) if the measurements number is large enough, consid ...

2019

We present an improved analysis of the Euler-Maruyama discretization of the Langevin diffusion. Our analysis does not require global contractivity, and yields polynomial dependence on the time horizon. Compared to existing approaches, we make an additional ...

2019

Efficient Learning from Comparisons

Lucas Maystre

Humans are comparison machines: comparing and choosing an item among a set of alternatives (such as objects or concepts) is arguably one of the most natural ways for us to express our preferences and opinions. In many applications, the analysis of data con ...

EPFL2018

Testing Graph Clusterability: Algorithms and Lower Bounds

Mikhail Kapralov, Aidasadat Mousavifar, Ashish Hari Chiplunkar

We consider the problem of testing graph cluster structure: given access to a graph G = (V, E), can we quickly determine whether the graph can be partitioned into a few clusters with good inner conductance, or is far from any such graph? This is a generali ...

IEEE COMPUTER SOC2018

Automated microfluidic sorting of mammalian cells labeled with magnetic microparticles for those that efficiently express and secrete a protein of interest

Amar Rida, Nicolas Mermod, Etienne Lançon, Niamh Harraghy

We developed a method for the fast sorting and selection of mammalian cells expressing and secreting a protein at high levels. This procedure relies on cell capture using an automated microfluidic device handling antibody-coupled magnetic microparticles an ...

Wiley2017

Safe Adaptive Importance Sampling

Martin Jaggi, Sebastian Urban Stich, Anant Raj

Importance sampling has become an indispensable strategy to speed up optimization algorithms for large-scale applications. Improved adaptive variants - using importance values defined by the complete gradient information which changes during optimization - ...

2017