Publications related to Taxonomy Induction Using Hypernym Subsequences

Related publications (20)

Genetic Algorithms for the Discovery of Homogeneous Catalysts

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas, Simone Gallarati, Puck Elisabeth van Gerwen, Alexandre Alain Schöpfer

In this account, we discuss the use of genetic algorithms in the inverse design process of homogeneous catalysts for chemical transformations. We describe the main components of evolutionary experiments, specifically the nature of the fitness function to o ...

2023

Early decoding of walking tasks with minimal set of EMG channels

Silvestro Micera

Objective. Powered lower-limb prostheses relying on decoding motor intentions from non-invasive sensors, like electromyographic (EMG) signals, can significantly improve the quality of life of amputee subjects. However, the optimal combination of high decod ...

IOP Publishing Ltd2023

Multi-armed Bandits in Action

Farnood Salehi

Making decisions is part and parcel of being human. Among a set of actions, we want to choose the one that has the highest reward. But the uncertainty of the outcome prevents us from always making the right decision. Making decisions under uncertainty can ...

EPFL2020

Benchmark for Bimanual Robotic Manipulation of Semi-deformable Objects

Aude Billard, Kunpeng Yao, Farshad Khadivar, Bernardo Fichera, Konstantinos Chatzilygeroudis, Ilaria Lauzana

We propose a new benchmarking protocol to evaluate algorithms for bimanual robotic manipulation semi-deformable objects. The benchmark is inspired from two real-world applications: (a) watchmaking craftsmanship, and (b) belt assembly in automobile engines. ...

2020

Asymptotic learning curves of kernel methods: empirical data versus teacher-student paradigm

Matthieu Wyart, Mario Geiger, Stefano Spigler

How many training data are needed to learn a supervised task? It is often observed that the generalization error decreases as n(-beta) where n is the number of training examples and beta is an exponent that depends on both data and algorithm. In this work ...

IOP PUBLISHING LTD2020

Distributed Learning over Networks under Subspace Constraints

Ali H. Sayed, Stefan Vlaski, Roula Nassif

This work presents and studies a distributed algorithm for solving optimization problems over networks where agents have individual costs to minimize subject to subspace constraints that require the minimizers across the network to lie in a low-dimensional ...

IEEE2019

Graph Spectral Clustering of Convolution Artefacts in Radio Interferometric Images

Paul Hurley, Matthieu Martin Jean-André Simeoni

The starting point for deconvolution methods in radioastronomy is an estimate of the sky intensity called a dirty image. These methods rely on the telescope point-spread function so as to remove artefacts which pollute it. In this work, we show that the in ...

IEEE2019

Language Independent Query by Example Spoken Term Detection

Dhananjay Ram

Language independent query-by-example spoken term detection (QbE-STD) is the problem of retrieving audio documents from an archive, which contain a spoken query provided by a user. This is usually casted as a hypothesis testing and pattern matching problem ...

EPFL2019

Localizing the Source of an Epidemic Using Few Observations

Brunella Marta Spinelli

Localizing the source of an epidemic is a crucial task in many contexts, including the detection of malicious users in social networks and the identification of patient zeros of disease outbreaks. The difficulty of this task lies in the strict limitation ...

EPFL2018

A Domain-Adaptive Two-Stream U-Net For Electron Microscopy Image Segmentation

Pascal Fua, Mathieu Salzmann, Pablo Marquez Neila

Deep networks such as the U-Net are outstanding at segmenting biomedical images when enough training data is available, but only then. Here we introduce a Domain Adaptation approach that relies on two coupled U-Nets that either regularize or share correspo ...

IEEE2018

Vision-Based Sense and Avoid Algorithms for Unmanned Aerial Vehicles

Steven Adriaan Roelofsen

The field of Unmanned Aerial Vehicles (UAVs), also known as drones, is rapidly growing, both in terms of size and of number of applications. Civil applications range from mapping, inspection, search and rescue, taking aerial footage, to art show, entertain ...

EPFL2017

Automated Taxonomy Induction and its Applications

Amit Gupta

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...

EPFL2017

Efficient greedy algorithms for high-dimensional parameter spaces with applications to empirical interpolation and reduced basis methods

Jan Sickmann Hesthaven, Benjamin Stamm

We propose two new and enhanced algorithms for greedy sampling of high- dimensional functions. While the techniques have a substantial degree of generality, we frame the discussion in the context of methods for empirical interpolation and the devel- opment ...

EDP Sciences2014

Population Sensing Using Mobile Devices : a Statistical Opportunity or a Privacy Nightmare?

Farid Movahedi Naini

In our daily lives, our mobile phones sense our movements and interactions via a rich set of embedded sensors such as a GPS, Bluetooth, accelerometers, and microphones. This enables us to use mobile phones as agents for collecting spatio-temporal data. The ...

EPFL2014

Lessons from Nature: Computational Design of Biomimetic Compounds and Processes

Ursula Röthlisberger, Pablo Campomanes Ramos, Elizabeth Claire Brunk, Negar Ashari Astani, Esra Bozkurt, Nicholas John Browning

Through millions of years of evolution, Nature has accomplished the development of highly efficient and sustainable processes and the idea to understand and copy natural strategies is therefore very appealing. However, in spite of intense experimental and ...

2014

Remote sensing image segmentation by active queries

Devis Tuia

Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained ...

2012

New Results in the Theory of Linear and Integer Programming

Nicolai Hähnle

The polynomial Hirsch conjecture states that the vertex-edge diameter of a d-dimensional polyhedron with n facets is bounded by a polynomial in d and n. For the special case where the polyhedron is defined as the set of points satisfying a system Ax ≤ b of ...

EPFL2012

Swift Algorithms for Repeated Consensus

André Schiper, Martin Hutle, Nuno Filipe de Sousa Santos, Fatemeh Borran

We introduce the notion of a swift algorithm. Informally, an algorithm that solves the repeated consensus is swift if, in a partial synchronous run of this algorithm, eventually no timeout expires, i.e., the algorithm execution proceeds with the actual spe ...

Ieee Computer Soc Press, Customer Service Center, Po Box 3014, 10662 Los Vaqueros Circle, Los Alamitos, Ca 90720-1264 Usa2010

Nonlinear Average Consensus

Martin Hasler, Leonidas Georgopoulos

We present an algorithm for nonlinear consensus in complex networks. Our motivation draws from analysis on the algorithm based on a weighted linear update protocol. Comparison of the asymptotic with early convergence rate encourages an alternative algorith ...

IEICE2009

A Frequency Domain Approach to Registration of Aliased Images with Application to Super-Resolution

Martin Vetterli, Sabine Süsstrunk, Patrick Vandewalle

Super-resolution algorithms reconstruct a high resolution image from a set of low resolution images of a scene. Precise alignment of the input images is an essential part of such algorithms. If the low resolution images are undersampled and have aliasing a ...

2006