output
20022025
most citedObservation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

10.9k citations

Showing 2017Show all

188 papers · 1 filter

cs.IR20172 cited

Predicting Relevance Scores for Triples from Type-Like Relations using Neural Embedding - The Cabbage Triple Scorer at WSDM Cup 2017

Yael Brumer, Bracha Shapira, Lior Rokach +1

The WSDM Cup 2017 Triple scoring challenge is aimed at calculating and assigning relevance scores for triples from type-like relations. Such scores are a fundamental ingredient for…

cs.DC20171 cited

Range Queries in Non-blocking -ary Search Trees

Trevor Brown, Hillel Avni

We present a linearizable, non-blocking -ary search tree (-ST) that supports fast searches and range queries. Our algorithm uses single-word compare-and-swap (CAS) operations…

cond-mat.quant-gas201746 cited

Vortex lattices in binary Bose-Einstein condensates with dipole-dipole interactions

Ramavarmaraja Kishor Kumar, Lauro Tomio, Boris A. Malomed +1

We study the structure and stability of vortex lattices in two-component rotating Bose-Einstein condensates with intrinsic dipole-dipole interactions (DDIs) and contact interaction…

astro-ph.EP201741 cited

A dearth of small particles in the transiting material around the white dwarf WD 1145+017

S. Xu, S. Rappaport, R. van Lieshout +35

White dwarf WD 1145+017 is orbited by several clouds of dust, possibly emanating from actively disintegrating bodies. These dust clouds reveal themselves through deep, broad, and e…

cs.LO20176 cited

Performance Heuristics for GR(1) Synthesis and Related Algorithms

Elizabeth Firman, Shahar Maoz, Jan Oliver Ringert

Reactive synthesis for the GR(1) fragment of LTL has been implemented and studied in many works. In this workshop paper we present and evaluate a list of heuristics to potentially…

cs.NE201744 cited

DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess

Eli David, Nathan S. Netanyahu, Lior Wolf

We present an end-to-end learning method for chess, relying on deep neural networks. Without any a priori knowledge, in particular without any knowledge regarding the rules of ches…